Value Of solar literature review

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Readers Please!![edit | edit source]

Any comments are welcomed on the Discussion page (tab on top left corner) including additional resources/papers/links etc. Papers can be added to relevant sections if done in chronological order with all citation information and short synopsis or abstract. Thank You.

LITERATURE REVIEW[edit | edit source]

The market value and cost of solar photovoltaic electricity production.[edit | edit source]

Borenstein S. The market value and cost of solar photo voltaic electricity production. Center for the Study of Energy Markets. 2008 Jan 14.

  • Valuation of Solar
  1. Value greatly depends on time of production, location of installation, and the direction in which the panel is facing.
  2. Production peaks disproportionately with the peak demand.
  • Advantages of solar
  1. Distributed PV installation does not require transmission and distribution infrastructure.
  2. Lack of transmission and distribution system reduces the losses that occur.
  3. As PV is a distributed system, it provides security to the entire network in the sense that the whole system won’t be affected if the PV system is targeted or fails.
  4. No emissions of greenhouse gases and other pollutants.
  • Reasons for Misvalue of PV
  1. Intermittency in supply
  2. A feeling that the transmission and distribution system would be required in the future and hence there is no saving in terms of cost in the real sense.
  3. Planning studies cannot be performed as there is no guarantee of how much solar power would be produced.
  4. If the output of PV changes then the second to second stability of the system changes rapidly.
  • Time Varying Production of solar PV
  1. PV production varies with season, latitude and direction of tilt of panels.
  2. There are two approaches to conceptualize the time varying production
    1. With a detailed and wide sample of data.
    2. Simulation data from TRNSYS (Transient System Simulation Program)
  • Real time prices for valuing the power from solar PV
  1. This can be done through two approaches
    1. Actual price from the market where it is used.
      1. Advantage
        1. The data would be credible as it is obtained from an actual market
      2. Disadvantage
        1. There could be regulation of prices, that is a price cap could be fixed.
        2. If there is excess production at peak demand period, the price would be relatively less as compared to if produced over time.
    2. Simulated data from a competitive market
      1. Here the model can be designed to decide the cap and hence there would be no regulation on the prices.
      2. This model is based on the import/demand supply as the production varies.
      3. It includes baseload cost+peakcost+mid-merit cost.
  • Correlation between prices and PV production
  1. PV production depends on weather.
  2. Demand depends on weather.
  3. Hence production depends on demand.
  4. However, this correlation could be misleading as weather condition may vary for the same system.
  • Time varying solar power
  1. The author calculates the results using 5 different price series, one is actual hourly spot price in the region, second is hourly spot price with the adjustment for low price caps, third is assumed demand and supply with some elasticity -0.025, fourth is with elasticity of -0.1 and fifth is when some capacity costs are recovered through non energy payments in whole sale market.
  2. The assumption of marginal cost never exceeding the highest cost of generation , shortfall being paid to generators, the revenue being recovered as uniform fee on KWh sold, is made.
  3. In comparison to the real time wholesale price , the simulated prices produce much larger differentials. In his simulations most of the generation costs are recovered through energy prices and not through capacity payments.
  4. He has concluded that value of electricity delivered from on site solar PV and its undervaluation depend on the direction of its orientation.
  5. Resource adequacy regulations assure that the system always has excess production capacity and consistent with this approach revenues for capacity payments to generators are collected from retail customers in a time invariant way, then wholesale prices will indicate that power at peak times is not much more valuable than off peak.
  • Effect of location on solar PV
  1. Solar PV brings reduced investment in transmission and distribution infrastructure.
  2. Solar PVs are usually installed in areas where T&D is constrained.
  3. State incentives are given to customers for installing PVs that are not in the service territories and no greater incentive is offered to the customers in the service area who install PVs.
  4. A carefully planned location based incentive would reduce transmission congestion and need for transmission infrastructure.
  5. PV is not abundant in most valued locations.
  • Economics of solar PV
  1. Two related issues in a cost analysis are the lifetime of the panels and the appropriate discount rate for evaluation of the project.
  2. The large cost that a owner would face for a PV installation would be replacing inverter.
  3. PV cell production declines eventually with the range of 1% of the original capacity per year.
  4. The soiling effect dirties the panel and it absorbs less solar radiation, hence less electricity.
  5. The net present cost of PV installation is more than the net present benefits of electricity it will produce.


  • Key Takeaways
Data considered in valuating Solar PV
Reduction on Transmission losses
Peak usage time saves
Fluctuation in solar PV production throughout the day (requires available data or simulation) - account for specific conditions of the installation
Environmental burden release and Social value (Not quantified in the paper)
All above data are location dependent
Analysis of solar value in residential homes (Bornstein 2007)
Analysis of solar value for industry and businesses (Wiser 2007)
Study is done in 2008 - Look for more recent articles in litterature on the subject.

Minnesota's Value of Solar[edit | edit source]

Minnesota's value of solar-can a norther state's new policy defuse distributed generation battles

  • What is Value of solar?

It is a concept of utilities paying fair and transparent price for solar energy produces by a domestic entity. The utilities in the US are pretty much doing that but not fairly. They are paying for the electricity that is being produced by the solar but not for the amount of pollution that is going down by not using the conventional source, the transmission and distribution capacity that is being avoided, the health issues that are declining, the operation and maintenance cost and many other aspects. The estimation of all these costs for 1 unit of electricity that is being supplied back to the grid by a producer is called the value of solar.

  • Why value of solar?

It is a fair and transparent way of deciding on the cost of solar. It is the answer to both the utilities and customers problems. This will compensate the solar producers well and also bring a long term stability. The concept utilities comply to is net metering, which blocks the actual value of solar as it is based on retail price. Net metering will force consumers to go beyond their actual solar capacity and also increase the consumption of energy.

  • What is net metering?

It is an arrangement where a customer receives full credit for whatever power they deliver to the grid.

  • Why net metering or NEM not fair?

The customer who zero out or null out their electricity bill, do not pay their fair share for the transmission and distribution infrastructure that they are using and hence other customers end up paying this.



  • Executive Summary

In March 2014, Minnesota became the first state to adopt a value of solar policy. It may fundamentally change the financial relationship between electric utilities and their energy-producing customers. It may also serve as a precedent for setting a transparent, market-based price for solar energy. This report explains the origins of value of solar, the compromises made to get the policy adopted in Minnesota, and the potential impact on utilities and solar energy producers.

  • Difference between VOS and Net Metering
  • Challenges encounter with the use of Net Metering
  • Benefits of VOS for Customer and Utility
  • Key Aspects and components of VOS
  1. Pollution sources avoided
  2. Peak energy needs furnished by supplemental power plants avoided
  3. Fixed price of long term energy provided
  4. Electric Grid Exhaustion reduction

Comparative assessment of net metering and feed in tariff schemes for residential PV systems[edit | edit source]

Poullikkas A. A comparative assessment of net metering and feed in tariff schemes for residential PV systems. Sustainable Energy Technologies and Assessments. 2013 Sep 30;3:1-8.

  • Feed-in-Tariff

Feed-in-tariff (FIT) scheme provide a guaranteed price to the solar producer. The utility is under obligation to purchase the electricity from the producers.

  • Net Metering

Net metering scheme employs a mechanism where producers are paid for the solar production based on whether electricity is being taken from the grid or it is being supplied to the grid. Time of the day net metering is based on the variation in rates during the day, month and season. Market rate net metering employs a rate which is some function of the market rate of electricity.

  • Myths about Net metering

Revenue of the utility decreases. It represents a subsidy from one group of customers to another. It burdens the smaller utilities.

  • Conclusion

Study in Cyprus for a typical rooftop PV system concluded that net metering performs better than the feed-in-tariff under certain conditions and especially when the electricity bill is taken into account.

Treatment of Solar Generation in Electric Utility Resource Planning[edit | edit source]

[Sterling J, McLaren J, Taylor M, Cory K. Treatment of Solar Generation in Electric Utility Resource Planning. National Renewable Energy Laboratory (NREL), Tech. Rep. 2013 Oct 1.]

  • Integrated Resource Planning (IRP)

It is a planning process done by utilities where a comprehensive study is conducted. The supply and demand evaluations are done and whether the energy requirements, peak demand and reserve capacity are met are also evaluated. The utilities usually do these studies for the long term future, generally for a period of 20 years. Renewable energy sources are also being included in these studies as some utilities feel that the more diversified the sources, the more economical it is from the financial point of view. However, the methods the various utilities use to conduct these studies vary widely. The resource planning for a long term is basically done in the flowing detailed manner

• Evaluate State Policies and Mandates

• Review Existing Generation Fleet

• Forecast Load

• Plan Capacity Expansion

• Production Cost Modeling

• Select Portfolio

  • Benefits and Challenges of Solar to include it in resource planning studies

Benefits •Meet renewable standard requirements

•Fuel diversification

•Cost stability

•Geographic dispersal benefits and modularity

•Partial correlation with peak demand

•Mitigation of environmental compliance risks

•Avoid line losses

Challenges •Variable and uncertain output

•Ramping issues

•Economics

•Lack of current capacity need

•Reduced capacity benefit over time with increasing solar penetration

  • Renewable Portfolio Standards (RPS)

Some states have a policy that they have to buy certain part of their total electricity sales from renewable sources.

  • Inclusion of Solar into IRP

This requires credible data for the following • Solar Profiles

• Solar Costs

• Solar Capacity value- The capacity value assigned to solar PV varies greatly from utility to utility. Some utility do not assign any capacity value to solar while others assign a value depending upon the type of PV system being used. • Additional considerations- These include Solar Integration Cost Customer sided generation- Whether DPV is to be considered as a net load or a source • Procurement Plan

  • Solar benefits according to Utilities

• Meeting renewable standards required

• Fuel Diversification

• Cost Stability

• Wide range of PV and its dispersal ability

• Partial correlation with peak demand

• Reduce environmental risks

• Avoided line losses

  • Challenges according to Utilities

• Variable and uncertainty in output

• High ramp up and ramp down rates

• Economics

• Lack of current capacity need- Due to RPS requirements by state, utilities are increasing capacity even though there is a load decrease

• Net Metering concerns

• Reduced value as the solar penetration increases

  • Utility Identified Analysis Needs

• Credible PV price and performance data

• Analysis of how to incorporate geographically diversified resources into modeling

• Analysis of the potential relationship between energy storage and PV

• Easier ways to predict impacts of increased PV penetration

• Better risk/uncertainty analysis methods

• Improved commercial production cost models

• Translate distribution system impacts to long-term plans

• Clarity about when to include distributed generation in supply modeling

Designing Austin Energy's solar tariff using a distributed PV value calculator[edit | edit source]

[Designing Austin Energy's solar tariff using a distributed PV value calculator]

  • Consequences of Net Metering

Solar customers size their solar systems according to their base load as they feel that the excess generation given back to the grid is being paid for at a low rate. Or the solar customers tend to use more energy because they feel that it is free consumption and if they were to give back to the grid they would only be paid at a low rate.

Austin Energy designed a new ‘Value of Solar’ rate. It is still avoided cost calculation at heart but compensates the solar customers at a more competitive price. The calculation tool values the following components :

• Loss savings- Calculated on an hourly basis. Takes into account the benefits provided by distributed sources of energy by producing energy at the same location where required.

• Energy savings-This is the PV output plus the loss savings times the marginal energy price

• Generation capacity savings-It is the effective load carrying capacity of PV times the cost of capacity

• Fuel price hedge value- It is the amount that would be incurred to eliminate the fuel price uncertainty

• Transmission and Distribution capacity savings =(T & D upgrade cost/ load growth) X term X T& D Factor

• Environmental benefits = PV output X Renewable Energy Credit price

The energy and generation capacity costs are reflected when a study of the relation between PV output and nodal prices is done.

After concluding that the average nodal price does not accurately represent the actual value of solar, a new value of solar termed as 'solar premium' was calculated which gave accurate credit to the customers for solar power generation, which was found to be higher than if the same amount of generated power was credited at the marginal electricity price of the area.

Austin Energy came up with the following residential rebate policy on the basis of some assumptions. This rebate was formulated to provide a temporary boost to adoption of solar power.

  • Rebate amount= PV rating (kWdc-stc) X Inverter Efficiency X Rebate level

This new value of solar approach is much more detailed and it gives fair incentives to the solar customers.



  • Citation

Rábago, Karl R, Leslie Libby, Tim Harvey, Austin Energy, Benjamin L Norris, Thomas E Hoff, and Soscol Ave. “DESIGNING AUSTIN ENERGY’S SOLAR TARIFF USING A DISTRIBUTED PV VALUE CALCULATOR,” n.d., 6.

  • Abstract

Austin Energy plans to offer residential customers a new solar net metering tariff based on the value of solar energy generated from distributed photovoltaic (PV) systems in the grid to the utility in place of traditional net metering. Austin Energy worked with Clean Power Research (CPR) to employ the algorithms from a utility value calculator to design the solar tariff. A rebate structure was also designed in order to ensure that customers still satisfy a key economic cost-effectiveness test and address first-cost barriers facing solar customers. These two revenue types – an ongoing credit for solar production, and a one-time rebate – begin a transition toward production-based incentives for residential customers based on actual value credits for solar generation and steadily declining up-front rebates.

Key Takeaways
Net metering under-represents the value of solar
Difficulties inherent in accurate calculation of cost of solar:
  1. Modeling PV generation for locations without solar ground measurements
  2. Ensuring that the modeled outputs cover specific hours in which coincident electric loads have been measured by the utility
  3. Calculating marginal line loss savings during those same hours
  4. Forecasting fuel prices
  5. Determining the effective capacity of PV by calculating hourly loss of load probabilities
  6. Applying principles of engineering economics

A REGULATOR'S GUIDEBOOK: Calculating the Benefits and Cost of Distributed Solar Generation[edit | edit source]

A Regulator's Guidebook: Calculating the benefits and cost of distributed solar generation

Calculating utility avoided cost

  • Avoided energy benefits
  1. Identifying the displaced marginal generation, which is the cost saved in avoiding the operation and maintenance of a simple cycle combustion turbine or combined cycle gas turbine for providing electricity. This unit would be produced by customer's solar generator.
  2. Value of avoided generation for the life period of a solar generation could be calculated by developing
    1. an hourly market price shape for each month.
    2. a forecast of annual average market prices in the future. This can be done by projecting the cost of marginal generation unit, O&M cost for it and degradation of heat rate. (Heat rate is the measure of efficiency by which a unit creates electricity by running fuel for heat to power a turbine)
  • Calculating system losses
  1. Solar generation when near the load avoids losses with delivering power over long distances. The excess produced by solar would be exported to the grid or to the neighboring customers, there by avoiding losses in the electricity that would have come from the central unit.
  2. On an average line losses are in the range of 7% and higher and "lost and unaccounted for energy" loss, these two may be avoided by solar generation.
  3. Because the losses are not uniform, calculating it on a marginal basis would be more accurate. It says about the correlation of solar PV to heavy loading periods (congestion and transformer thermal conditions increase losses).
  • Calculating generation capacity.
  1. Capacity value exists when a utility can rely on a generating unit to meet its peak demand there by avoiding purchasing of electricity to meet the peak load.
  2. The intermittency problem is solved by
    1. Recognizing a capacity value for intermittent resource and call it effective load carrying capability. This is a statistical method that provides reliable data to project the capacity of intermittent resources.(effective load carrying capability of a generating unit is load increase that system can carry while maintaining designated reliability criteria)
    2. EELC is very data extensive, so a simpler method like projection from utility's load duration curve, by looking at top 50 load hours.
  3. The valuation of incremental capacity is small when compared to the utility where one unit of combined cycle gas turbine can add 500MW at once. One solution to this is a mix of short run and long run avoided capacity costs are applied to renewable generators based on the fact that no additional capacity would be required until a year called resource balance year. It is the utilities job to predict load growth and involve the solar generations in the system.
  4. The best approach would be to determine the capacity credit by looking at the capital and O&M cost of the marginal generator. This resulting value is capacity credit i.e. a credit for the utility capacity avoided by solar generation.
  5. Once effective load carrying capability is determined for a solar generation for a given utility, the calculation of generation capacity becomes easy. The capacity credit is the capital cost of the displaced unit times the effective capacity provided by PV.
  • Calculating transmission and distribution capacity.
  1. Solar generation is usually located at the site of load and helps reduce the congestion and wear&tear of transmission and distribution resources.
  2. To determine the ability of solar generation to defer T&D capacity conditions, we must have the current information on the system planning activities and periodically update this information. Also the investment trends must be extended to match the expected life of solar generation.
  3. With all this data in hand the T&D saving can be determined in two steps:
    1. First perform the economic screening of the areas to determine the cost of expansion and load growth rates for each area.
    2. Second would be to perform the technical load matching for most promising locations.
  4. By looking at the load profile for a year, peak days at the circuit and substation level can be isolated and capacity credit can be calculated. Reducing peak loads would sure avoid investments on overloading transformers, substations etc.
  5. Deferring an upgrade saves utility expenditures and atleast to some extent debt financed.
  6. Ideally the utilities will collect location specific data that support individual assessment of solar generation. In the absence of such data, system wide estimation of T&D deferral value is done.
  7. System wide deferral can be calculated by allocators to assign capacity value of specific hours in the year and then allocates estimates of marginal T&D costs to hours. T&D allocators are based on local loads and T&D cost would be allocated to the hours with the highest load. This approach lacks the potential to capture exact and location specific deferral potential but it does approximate some value without requiring extensive project planning cost and load data for specific feeders, circuits and substations.
  • Calculating grid ancillary services.
  1. Ancillary services in the grid usually include VAR support and voltage ride through.
  2. A solar generation would have inverters to change DC to AC with output at a specified voltage and without reactive power.The functionality of inverters are to disconnect in the event of circuit voltage above or below limits, a voltage dip from the utility can cause thousands of inverters disconnecting the solar generations.
  • Calculating financial services: fuel price.
  1. solar generation reduces the reliance on fuel sources that are at a risk of shortage and price volatility. It is also a fence against regulation of green house gases which greatly impact fuel prices.
  2. The risk of fuel price volatility is usually borne by customers as utilities are not doing enough to mitigate this risk. Reducing this risk has a value to utility customers even if utilities do nothing about it.
  3. For performing this calculation for each year that solar generation isolates the risk premium and helps avoid purchases that involve the risk premium.
  4. The risk premium of natural gas is the difference between major fuel price uncertainty and the one without any uncertainty.
  • Calculating financial service: market price response.
  1. Solar generations reduce the demand in peak hours, when price of electricity is highest.It also reduces over all load on the system and the amount of energy and capacity purchased.
  2. The expenditure on energy and capacity is the current price of power times the current load at any given point in time. The amount of load affects the price of the power, a drop in load would mean reduced market price which could be the result of a distributed solar generation.
  3. The total value of market price reductions can be calculated by summing up all the savings made over all periods of time during which solar was operated.
  • Calculating security services: reliability and resiliency.
  1. This value is difficult to quantify. It depends on a lot of assumptions made on risk of extended blackouts, cost to strengthen the grid, ability of solar to strengthen the grid.
  2. In a place crucial place like hospital in contingency situations, a traditional backup generator can be supported with a solar instead of relying entirely on traditional generation and fuel supply.
  3. Solar can be counted as a way of providing high reliability to vulnerable customers there by reducing the reliability costs of utility.
  • Calculating environmental services.
  1. Utility avoided compliance cost:
    1. The cost of complying to the environmental requirements is a real operating expense and can be considered as avoided cost of generation.
    2. Utilities with renewable portfolio standards avoid compliance cost due to solar generations.
    3. Quantification of social benefits is difficult. For example if a utility avoids production of 20MWh of conventionally produced electricity with solar then it also avoid paying for the emission clean up. But even if it produces that 20MWh conventionally the emissions would have got past the required emission controls. Not emitting this pollution is a significant benefit for the environment and society.
  2. Airborne emissions other than carbon and health benefits:
    1. The public health impacts of fossil fuel generation have been well documented. Air pollution increases severity of asthma attacks and other respiratory illnesses. Also the crops and forest lands get destroyed due to these emissions.
    2. Solar reduces fossil fuel generation from plants that emit high pollution during startup.
    3. To capture the benefits of solar emissions of carbon and other matter based on green energy pricing programs cost can be done.
  3. Avoided water pollution and conservation benefits:
    1. Utilities consume a tremendous amount of water each year and will be increasing. With solar this risk can be avoided , safe and affordable supplies can be assured to the customers of utility.
  • Calculating social services: economic development.
  1. Solar industry can create number of jobs and generate revenue locally. Growing demand of rooftop solar panels and supplies creates tax revenue at the state and local levels.
  2. Assumptions about construction of solar PV that it involves higher local jobs than a construction of CCGT plant and then net local benefit of solar on the economy can be calculated.


  • Citation

Keyes, Jason B., and Karl R. Rábago. “A REGULATOR’S GUIDEBOOK: Calculating the Benefits and Costs of Distributed Solar Generation.” Interstate Renewable Energy Council, Inc., October 2013. https://irecusa.org/publications/a-regulators-guidebook-calculating-the-benefits-and-costs-of-distributed-solar-generation/.

Solar Valuation and the Modern Utility's Expansion into Distributed Generation[edit | edit source]

Blackburn G, Magee C, Rai V. Solar valuation and the modern utility's expansion into distributed generation. The Electricity Journal. 2014 Feb 28;27(1):18-32.


This paper discusses why the net metering scheme is unfair to the utilities as well as to the non-solar customers. Net metering cause cross subsidization, that is it imposes a higher cost on certain customers to reduce the cost of electricity of other customers. Here it is the non-solar customers that end up paying more. The irony is that most of the solar customers adopt DPV because they have a higher demand, and ultimately they end up paying lesser as compared to someone who has a lower demand. From the utility perspective, the recovery of fixed costs from the net metering scheme is not possible. The solar customers are being paid at the retail rate for the electricity that they generate. The PV penetration levels are also very important as a high penetration market would require some upgradation or building of the transmission and distribution infrastructure to supply the excess power to the grid. So how can the capital for such an investment be recovered from? Another aspect is most of the protection infrastructure has not been designed for bi direction flow of current. So again if high PV penetration levels exists, it could induce more expense rather than benefits. So the paper basically looks for an alternative approach to the unfair net metering approach. The paper does a survey to study the evolving relationship between NEM and solar valuation. The survey seeks to understand a given utility's

  1. service territory and its consumer base
  2. observed financial impact associated with residential solar generation
  3. methods for recovering fixed costs

The following relationships were explored:

• Utility perception of distributed solar's financial impact on the following aspects of the organization's infrastructure and operations

• Voltage variability—the cost versus savings impact on grid voltage

• Generation capacity—the cost versus savings impact on generation capacity to the system

• Line loss—the cost versus savings impact on system energy losses

• Wholesale energy purchases—the cost versus savings impact on wholesale energy purchases

• Transmission and distribution (T&D) capacity—the cost versus savings impact on capital investments to the T&D system

The survey shows the most of the utilities feel that they are attributing a higher value to solar that what is needed. Also the PV penetration levels greatly influence the value of solar. There is great uncertainty about the success of the solar valuation techniques currently being employed. More cost and benefit analysis needs to be done by utilities to evaluate the true value of solar just as they do for conventional sources. There is a long way to go in reaching a consensus on the actual value of solar and it is quite possible that the VOS tariff policy as implemented in Austin is the way to go.

Value of Solar: Program Design and Implementation Considerations[edit | edit source]

[Value of Solar: Program Design and Implementation Considerations. Golden, CO: National Renewable Energy Laboratory. Accessed October. 2015 Mar 1;15:2015.]

This paper basically investigates and discusses various methods through which a VOS policy can be designed. Various design consideration can be evaluated. However, first one must consider the type of market where the program is to be implemented.

  • What is levelized cost of electricity (LCOE)?

It is defined as the project’s total cost of operation divided by the energy generated. LCOE= total life cycle cost/ total lifetime energy production

So there can be three types of markets depending on the LCOE and VOS values

• Price support market ( LCOE > VOS)

• Transitional market (LCOE=VOS)

• Price competitive market (LCOE < VOS) An analysis shown by NREL shows that without state and federal incentives for solar programs, all the states in USA fall in the price support market category.

The paper also discusses the case studies in Austin where a VOS policy has been implemented and the Minnesota VOS, where the policy has not yet been adopted by any utility. The one key difference between the two is that in Austin, the VOS rate will be reviewed annually while in Minnesota the VOS rate would be fixed for a period of 25 years. But the VOS rates would be reviewed annually for the new customers.

The paper also talks about possible changes and improvements that could be considered while adopting a VOS policy. VOS Program Design Considerations These can be broadly divided into the following

• Balancing design decisions: Setting objectives, understanding the design and stakeholders interest and placing the program needs in the context of what can be a rapidly changing market

• Installation details: Covering the installation rules for participants

• Rate and Contract treatment: Establish how VOS would be implemented over a long term project

• Price Supports: Considering an additional incentive on top of the VOS rate

• Administrative Issues: Thinking through the internal utility program operations and accounting

  • VOS features

The VOS rate is determined by

• Identifying the categories in which solar provides both benefit and cost to the utility and society

• Calculation value of each category (could be negative or positive)

• Combining the above components into a single rate


Here the paper presents two hypothetical examples of utilities for each of the above points and does a thorough analysis of how the VOS design would change depending on the utility. The paper basically presents provides a framework for a VOS design for the customers, stake holders, utilities and interested parties.

Methods for Analyzing the Benefits and Costs of Distributed Photovoltaic Generation to the U.S. Electric Utility System[edit | edit source]

Denholm P, Margolis R, Palmintier B, Barrows C, Ibanez E, Bird L, Zuboy J. Methods for Analyzing the Benefits and Costs of Distrubuted Photovoltaic Generation to the US Electric Utility System. National Renewable Energy Laboratory; 2014 Sep 1.

This report examines the methods to estimate the value of DGPV. The report classifies the sources of DGPV benefits and costs into the following categories

  • Energy- The report proposes 5 approaches given below to calculate the avoided energy cost

[1] Simple avoided generator—assumes PV displaces a typical “marginal” generator, such as a combined-cycle gas turbine (CCGT) with a fixed heat rate

[2] Weighted avoided generator—assumes PV displaces a blended mix of typical “marginal” generators, such as a CCGT and combustion turbines (CTs)

[3] Market price—uses system historic locational marginal prices (LMPs) or system marginal energy prices (system lambdas) and PV synchronized to the same year

[4] Simple dispatch—estimates system dispatch using generator production cost data

[5] Production simulation—simulates marginal costs/generators with PV synchronized to the same year.

  • Environment- This mainly deals with the cost of avoided emissions that may occur depending on the generating source
  • T & D losses- This basically depends on the location of the DGPV. Again some of the proposed methods are

[1] Average combined loss rate—assumes PV avoids an average combined loss rate for both T&D

[2] Marginal combined loss rate—modifies an average loss rate with a non-linear curve-fit representing marginal loss rates as a function of time

[3] Locational marginal loss rates—computes marginal loss rates at various locations in the system using curve-fits and measured data

[4] Loss rate using power flow models—runs detailed time series power flow models for both T&D.

  • Generator capacity-Estimating the generation capacity value of DGPV requires calculating the actual fraction of a DGPV system’s capacity that could reliably be used to offset conventional capacity and also applying an adjustment factor to account for T&D losses. The report discusses the following four methods for estimating generation capacity value:

1. Capacity factor approximation using net load—examines PV output during periods of highest net demand

2. Capacity factor approximation using loss of load probability (LOLP)—examines PV output during periods of highest LOLP

3. Effective load-carrying capacity (ELCC) approximation (Garver’s Method)—calculates an approximate ELCC using LOLPs in each period

4. Full ELCC—performs full ELCC calculation using iterative LOLPs in each period.

  • T & D capacity- DGPV can affect both the congestion and the reliability of the system. The report covers the following three methods for estimating transmission capacity value:

1. Congestion cost relief—uses LMP differences to capture the value of relieving transmission constraints

2. Scenario-based modeling transmission impacts of DGPV—simulates system operation with and without combinations of DGPV and planned transmission in a PCM

3. Co-optimization of transmission expansion and non-transmission alternative simulation—uses a transmission expansion planning tool to co-optimize transmission and generation expansion and a dedicated power flow model to evaluate proposed build-out plans.

The report describes the following six methods for estimating distribution capacity value:

1. PV capacity limited to current hosting capacity—assumes DGPV does not impact distribution capacity investments at small penetrations, consistent with current hosting capacity analyses that require no changes to the existing grid

2. Average deferred investment for peak reduction—estimates amount of capital investment deferred by DGPV reduction of peak load based on average distribution investment costs

3. Marginal analysis based on curve-fits—estimates capital value and costs based on nonlinear curve-fits; requires results from one of the more complex approaches below

4. Least-cost adaptation for higher PV penetration—compares a fixed set of design options for each feeder and PV scenario

5. Deferred expansion value—estimates value based on the ability of DGPV to reduce net load growth and defer upgrade investments

6. Automated distribution scenario planning (ADSP)—optimizes distribution expansion using detailed power flow and reliability models as sub-models to compute operations costs

  • Ancillary services- These services are required to maintain the reliability of the grid. It mainly includes voltage control and operating reserves. Three methods are discussed to estimate theses services

1. Assume no impact—assumes PV penetration is too small to have a quantifiable impact

2. Simple cost-based methods—estimates change in ancillary service requirements and applies cost estimates or market prices for corresponding services

3. Detailed cost-benefit analysis—performs system simulations with added solar and calculates the impact of added reserves requirements; considers the impact of DGPV providing ancillary services

  • Other factors- These mainly deal with the fuel price uncertainty and also reduction in energy prices when DGPV is connected to grid

The report provides a possible framework to work with to calculate each of the parameters. The figure gives a very precise idea to utilities ,stakeholders and parties involved on how to develop a framework that would quite accurately determine the value of solar.

Possible flow of an integrated DGPV study.jpg

The Value of Distributed Solar Electric Generation to New Jersey and Pennsylvania[edit | edit source]

Perez R, Norris BL, Hoff TE. The value of distributed solar electric generation to New Jersey and Pennsylvania. Clean Power Research. Prepared for the Mid-Atlantic and Pennsylvania Solar Energy Industries Associations. 2012 Nov.

In this report the VOS analysis is done at seven locations, four in Pennsylvania and three in New Jersey. These locations were chosen because they differ in generation mix and this would be reflected in the different environmental costs. Also they differ in the solar radiation levels. Each location was studies for four types of PV configurations which are as follows

• South-30 (fixed)

• Horizontal (fixed)

• West-30 (fixed)

• 1-Axis (tracking at 30-degree tilt)

This provided a difference in the solar production levels and hence were reflected in the capacity avoided cost and also the energy costs avoided. The detailed calculations as to how the numbers were obtained is also explained in this paper. Some of the key takeaways and conclusions were as follows

[1] Total Value :This value varied from 256/ MWh to 318/MWh

[2] Energy Value: This mainly consists of the fuel cost savings and the operation and maintenance cost saving when a PV system is used in place of a conventional power plant (Typically a combined cycle gas turbine )

[3] Strategic Value: This is mainly the security value that a DPV system brings as it is not concentrated at one place. It also includes the Long term value that it brings to the society at large

[4] Market Price reduction: The highest values were obtained in locations where there was a very good match between the Location Marginal Price (LMP) curve and the PV output curve

[5] Environmental Value: This too varied depending on the types of generation the PV was to be replaced with

[6] T & D capacity Value: The values were fairly low as the study only takes into consideration the infrastructure capital that would be deferred for a future time and not immediate investment that would be saved

[7] Fuel Price Hedge: This value essentially determines the future avoided purchases of fuel. So the value greatly depends on the studies utilities or integrated resource planning

[8] Generation capacity Value: As there is a moderate match between the PV output and the load, this value is typically taken between 28-45% of the rated PV output

[9] Economic Development Value: PV generation provides local jobs at higher rates than conventional generation

[10] Solar Penetration Cost: As the solar market penetration increases, more and more infrastructure would be required to synchronize it with the grid. This is actually an estimated expense and hence it is given a negative value

Environmental impacts from the solar energy technologies[edit | edit source]

Environmental impacts from the solar energy technologies

Environmental impacts from solar energy technologies

This paper basically talks about the impacts that solar energy production potentially has, positive and negative. The positive effects of solar technology are always more propped up and talked about. There is not much discussion about its negative repercussions on the environment. This paper tries to rectify that missing component in the discussion around solar energy. It discusses the impacts of Solar PV and Solar thermal technologies. Some of the negative impacts of using solar energy on the environment are as follows :

• Visual Impact

• Routine and accidental release of chemicals

• Land use

• Work safety and hygiene

• Effect on ecosystem

• Impact on water resources

However, all these problems can be overcome by proper site selection, design, innovation and focus on health and safety. The negative impacts of solar technologies are far lesser than that of conventional generation methods.

Impacts of High Solar Penetration in the Western Interconnection[edit | edit source]

[Lew D, Miller N, Clark K, Jordan G, Gao Z. Impact of high solar penetration in the western interconnection. Contract. 2010 Dec;303:275-3000. ]

This paper gives a very detailed study of how solar penetration levels greatly impacts the interconnected grid. As more and more solar generation is being employed, its impact on the existing infrastructure also becomes important. It also examines if it is economically feasible for the western grid to accommodate more levels of solar penetrations. Typical studies are done for 5 % and 25 % solar penetration levels. The paper shows the day daily, seasonal and annual characteristics of Concentrating solar power (CSP) and Photovoltaic Solar (PV) for the areas considered in the study. It is seen that the CSP has a profile which is closer to the load profile. One key finding is that the variable cost goes down as solar penetration reaches 25 %. This is obvious because this is the value of the fuel that is being displaced. However, the operational cost reductions tend to go up as the solar penetration levels increases. This is due to the fact that additional solar power means additional capital investment. The generation being fixed we are just adding an extra source into the system, which ultimately is being added to the cost of the solar energy.

Effect of Penetration on Capacity Value

The capacity value of solar decreases with increased penetration. This is because when an adequate system is fed with more power from a similar source, it gives diminishing returns

Key Findings

The key finding of the study is that the western grid can accommodate 25% solar penetration if the following changes could be made over time • More transmission utilization

• A more thorough unit commitment and economic dispatch of the generators

• Develop very accurate forecasting mechanisms for solar power

• Build more transmission infrastructure as the renewable energy expands

• Detailed study and commitment of adequate operating reserves

• Increase the flexibility of the existing generators

Electricity Rate Structures and the Economics of Solar PV:Could Mandatory Time-of-Use Rates Undermine California’s Solar Photovoltaic Subsidies?[edit | edit source]

Borenstein S. Electricity Rate Structures and the Economics of Solar PV: Could Mandatory Time-of-Use Rates Undermine California’s Solar Photovoltaic Subsidies?. Center for the Study of Energy Markets. 2007 Sep 17. This paper evaluates the validity of the claim that Time Of Use (TOU) tariff caused the orders for solar installations by 78 % as published in the Los Angeles Times in May 2007.

In January 2007, there was a requirement for solar customers to switch to the TOU tariff from the fixed rate tariff. The paper does a thorough study of customers from two of the biggest utilities in California, Pacific Gas and Electric (PG&E) and Sothern California Edison (SCE). The paper does a calculation of the bills the customers would get. It initially calculated the bill under the fixed tariff mechanism and then with the TOU mechanism. Then the bill is calculated taking into consideration a 2 KW solar generation. The author makes various assumptions in these calculations. One critical aspect was that the TOU scheme was not the same in the two utilities. TOU is a mechanism where the price of electricity varies according to the demand and the time of the day. The fixed rate tariff is a tiered tariff mechanism where customers under a particular total consumption will pay a fixed amount as their bill.

Results

The study showed that the TOU tariff was in fact working more efficiently from the economic point of view for PG&E customers. The bills of these customers with and without a solar generation was lesser as compared to the fixed tariff bills. However, SCE has a somewhat complex TOU tariff mechanism. They implement two different TOU schemes, one for customers with annual consumption of 4800-7200kWh (medium sized), and the other for customers with an annual consumption of more than 7800kWh (large sized). Now here to calculate the bills under such complex tariff schemes the author makes some valid assumption. The results however, show that for SCE customers with lower consumption, the fixed tariff scheme is better. While SCE customers with higher consumption will benefit from the TOU scheme. The paper however, clearly states that this has nothing to do with the decrease in solar orders. This is only because of some weird TOU tariff scheme that SCE is employing.

The paper concludes that the claims by Los Angeles Times are unsubstantiated and there could be a variety of different economic and social factors as well as comparing of wrong sets of data sets that may have caused them to come up with such a report.

Combined Optimal Retail Rate Restructuring and Value of Solar Tariff[edit | edit source]

Negash AI, Kirschen DS. Combined optimal retail rate restructuring and value of solar tariff. InPower & Energy Society General Meeting, 2015 IEEE 2015 Jul 26 (pp. 1-5). IEEE. This paper proposes a new approach to value solar power. It discusses about the problems with net metering as the number of solar customers are increasing. It also describes the Value of Solar approach and the potential downsides it has.

Three Part Retail Rate

The author proposes a new optimized retail rate called the three part retail rate. This attempts to recover variable costs and fixed costs of generation. Here energy cost is considered variable and customer costs is fixed. Also and additional variable charge is assumed for the demand.

Weighted Retail Rate VOST

It is proposed that the value of solar be linked to the proportion of each of the utilities cost components. Each of these cost components would be weighted by a factor that represents the efficacy of the distributed solar to reduce those costs. An optional external component rate ‘v’ could be added to the weighted retail rate.

VOST = (reng X w1) + (rdmd X w2) + (rcust X w3) + v

Where, reng ,rdmd and rcust are the utility’s energy, demand and customer cost components respectively of the retail rate and w1, w2 and w3 are the PV owner’s energy, demand and customer cost weights respectively.

A case study was done on a medium sized utility using the proposed approach and the results were found to be quite efficient and accurate. The increasing penetration of solar energy will force stated into making policies which are more fair and accurate. The techniques employed in this paper may be a way to go.


Valuing Distributed Energy: Economic and Regulatory Challenges[edit | edit source]

Valuing distributed energy: economic and regulatory challenges

  • The advancements and cost reductions in solar panels, smart meters and battery storage is facilitating cost reductions and smarter infrastructure. Solar can benefit the customers and the power system is an accepted fact but at the same time there are concerns about valuation, integration and operational cost allocation and recovery.
  • Following major concerns are addressed in the paper
  1. Starting a dialogue between all the stake holders in this.
  2. Why is there a need of new valuation approach.
  3. Explain the various benefits and costs of generation.
  4. How to measure the benefits by solar generations.
  • For sure all the distributed energy resources do one thing and i.e.reduce or shift the load. This alone creates economic tensions in the system.
  • There are many kinds of distributed energy but solar has been the most significant of all because of the drop in cost by 70% over a couple of years, fall in system price by 33% over just 2 years and introduction of third party ownership or leasing.
  • Current Valuation methods of solar:
  1. Public Utilities Regulatory Policy Act 1978 [1] was the starting point of this pricing mechanism. It required utilities to purchase power from customers producing it at avoided cost. Though a lot of utilities contrived through it, but it still is useful in evaluating options for distributed energy pricing and also many new policies use PURPA's legal foundation.
  2. Proxy Unit Methodology:In this method an assumption is made that utility is avoiding a generating unit by using the solar power from customers. Then the fixed cost of this hypothetical unit becomes the avoided capacity cost and variable cost.
  3. Peaker Unit Methodology:This assumes that a customer generating by solar energy helps utility avoid paying for marginal generating unit. Here the capacity payment is based on fixed cost of the utilities least cost peaker unit and energy payments are the foretasted payments for a peaker unit over the contract period.
  4. Differential Revenue Requirement:The difference in cost for a utility with the customer producing by solar.
  5. Market Based Pricing:Customer with access to markets receive energy and capacity payments at market rates.
  6. Competitive Bidding:An open bidding process and winning bid is regarded as the utilities avoided cost.
  7. All the above methods have loop holes and following factors along with the above can be considered in the valuation process:
    1. Dispatch ability and minimum availability.
    2. Line loss and avoided transmission costs.
    3. Environmental cost adders.
    4. Long term levelized contract rates Vs varying rates.
    5. Resource Differentiation.
  • Location will surely determine the value of energy displaced, capacity and reserve requirements, factors used to determine congestion, loss in the T&D and externalities to be included in the pricing mechanism.
  • Short term transactions Vs long term contracts.A long term contract would help in addition of solar PVs over time when compared to short term pricing mechanism.
  • Uncertainty and Variability, A solar array paired with storage can reduce the variability and provide value for both customer and utility.
  • Pecuniary Vs non-pecuniary costs and benefits, Pecuniary elements are those that have direct cost benefit to someone who is party to the electricity transaction and non pecuniary are the benefits that are outside the transactions.
  • Building up a valuation model:
  1. Choosing the right energy value
  2. Choosing the right capacity value
  3. What are the pecuniary costs borne by others?
  4. What non-pecuniary costs and benefits exist?

Market value of solar power: Is photovoltaics cost competitive?[edit | edit source]

Hirth L. Market value of solar power: Is photovoltaics cost-competitive?. Renewable Power Generation, IET. 2015 Jan 1;9(1):37-45.

This paper reviews the economics of solar power acting as a source in the interconnected grid.

The costs of solar power have declined very steeply in the past decade. There is a lot of discussion regarding how the economic value of solar should be calculated.

The grid parity technique, comparing generation costs to the retail price, is an often used yet flawed metric for economic assessment, as it ignores grid fees, levies, and taxes.

It also fails to account for the fact that electricity is more valuable at some points in time and at some locations than that at others.

A better yardstick than the retail price is solar power’s ‘market value’.

The paper does a detailed study on how such a market value of solar can be obtained.

A Review of Solar PV Benefit & Cost Studies[edit | edit source]

Hansen L, Lacy V, Glick D. A review of solar PV benefit & cost studies. Boulder, CO: Rocky Mountain Institute. 2013.

Solar PV pricing has become a highly debated topic recently because of the growing number of Distributed Solar PV customers. The net metering scheme has not been accepted as fair by some utilities and so all stakeholder in DPV system are looking for alternatives. The Value of Solar (VOS) method is gaining popularity and extensive studies are being done in this regard. In VOS the cost attributed to solar is a combination of various avoided cost if PV is used instead of a conventional power plant.

The VOS is evaluated based on the following costs

• Energy cost

This includes avoided energy due to fuel, operation and maintenance and heat. It also includes the avoided system losses due to the reduced generation capacity and emissions.

• Capacity (generation, transmission and distribution)

This includes the generation avoided and hence the avoided infrastructure upgrades needed.

The DPV capacity is determined through its Effective Load Carrying Capacity (ELCC) , that is the demand that a DPV can cater to when operating at full capacity.

• Grid support services

This includes the reactive power and voltage supply, frequency regulation, energy imbalance and operating reserves.

• Financial risk

This value is positive when the introduction of DPV reduces the financial risk or overall market price. There is a fuel uncertainty value, which is the future uncertainty in fuel cost called the fuel price hedge. There is reduced demand because of lesser dependence on central generation.

• Security risk

There is lesser congestion in transmission and distribution. Only some area is affected when there is an outage of a PV plant. Back service can be kept available during outages.

• Environmental cost

This value is positive when it results in reduction of environmental or health impacts. It also includes a Renewable Portfolio Standard Cost, which is the cost saved through not using some other renewable source.

• Social costs

It results in increase in employment opportunities and accelerates economic development. There is a broad consensus as far as the energy cost avoided is concerned among the stakeholders. There is also some agreement on the capacity value of DPV. The key differences are in evaluating the values of security risk, financial risk, environment, society and grid support.

Why does VOS evaluations differ?

This is predominantly due to the fact that every utility would adopt a different approach to determine each of the components. For example, some may include capacity value in energy price and some may not.

This report hence gives us a framework on how each component of the VOS can be calculated.

An Evaluation of Solar Valuation Methods Used in Utility Planning and Procurement Processes[edit | edit source]

Mills AD. An evaluation of solar valuation methods used in utility planning and procurement processes. InAmerican Solar Energy Society (ASES) Annual Meeting, Baltimore, MD, April 16-20, 2013 2014 Apr 21.

As renewable technologies mature, recognizing and evaluating their economic value will become increasingly important for justifying their expanded use. This paper reviews a recent sample of U.S. load-serving entity (LSE) planning studies and procurement processes to identify how current practices reflect the drivers of solar’s economic value.

General planning process adopted by many LSEs

  • Assessment of future needs and resources
  • Creation of feasible candidate portfolios that satisfy needs
  • Evaluation of candidate portfolio costs and impacts
  • Selection of preferred portfolio
  • Procurement of resources identified in preferred portfolio

Key take aways

  • Full evaluation of the costs & benefits of solar requires that a variety of solar options are included in diverse set of candidate portfolios
  • Design of candidate portfolios, particularly regarding the methods used to rank potential resource options, can be improved
  • Studies account for the capacity value of solar, though capacity credit estimates with increasing penetration can be improved
  • Most LSEs have the right approach and tools to evaluate the energy value of solar. Improvements remain possible, particularly in estimating solar integration costs used to adjust energy value
  • T&D benefits, or costs, related to solar are rarely included in studies
  • Few LSE planning studies can reflect the full range of potential benefits from adding thermal storage and/or natural gas augmentation to CSP plants
  • The level of detail provided in RFPs is not always sufficient for bidders to identify most valuable technology or configurations


Value of Solar PV Electricity in MENA Region[edit | edit source]

Breyer C, Gerlach A, Beckel O, Schmid J. Value of solar PV electricity in MENA region. InEnergy Conference and Exhibition (EnergyCon), 2010 IEEE International 2010 Dec 18 (pp. 558-563). IEEE. This paper talks about how solar PV can be a success in the Middle Eastern and North African (MENA) Region

There is huge dependence on oil and natural gas for electricity generation in the MENA region. This is due to the fact that there is abundant supply of oil in this region. The paper predicts that by mid 2010 the cost of solar energy would be at par with the conventional energy.

The MENA region is a very sunny area. Historic PV diffusion can be separated into four major diffusion phases: 1st powering of satellites, 2nd off-grid applications, 3rd grid-parity of on-grid roof-top systems and 4th fuel-parity of PV power plants. PV systems are already the least energy cost option for satellites and off-grid solutions in sunny regions .

Capital expenditures for PV systems are derived from the empirical experience curve for PV, which depends on the growth rate of global PV markets and hence, on time and the general energy markets The paper shows that as more and more PV energy is being installed, the cost of this energy reduced.

Excellent solar resources and constant reductions in PV LCOE steadily establish new and fast growing markets for PV systems in MENA region. Up to 25% of total electricity market in MENA region might be addressable by PV as a consequence of PV gridparity for end-users. Low end-user prices are a consequence of widely granted energy subsidies in MENA region. These public costs can be internalized within the fuel-parity concept. Highly competitive PV power plants already achieve parity to oil power plants on a total cost basis and will reach fuel-parity only a few years later. Most oil and natural gas fired power plants will be beyond fuel-parity by 2020 in MENA region

2014 Value of Solar at Austin Energy[edit | edit source]

Clean Power Research (CPR). (2013). “2014 Value of Solar at Austin Energy.” Austin Energy.

This paper is an extension of the study that Austin power initially conducted in 2012 to implement the Value of Solar tariff to its customers. Again here , the Value of solar is calculated taking into consideration the current scenario. The VOS policy in Austin is such that it will be reviewed annually and hence a study will be conducted every year to determine the new VOS rate.

VOS Components

  • Guaranteed Fuel Value-Cost of fuel to meet electric loads and T&D losses inferred from nodal price data & guaranteed future Natural Gas prices
  • Plant O&M Value-Costs associated with operations and maintenance
  • Generation Capacity Value-Capital cost of generation to meet peak load inferred from nodal price data
  • Avoided T&D Capacity Cost-Cost of money savings resulting from deferring T&D capacity additions capacity additions
  • Avoided Environmental Compliance Cost-Cost to comply with environmental regulations and policy objectives

All of the above calculations are done in a detailed manner. The rates calculated are found to be lesser than the previous year. The possible reasons for this are

  • Natural gas prices have declined
  • Assumed life is 25 rather than 30 years

ƒ*Loss savings are slightly lower

ƒ*Transmission savings results have increased

ƒ*Calculation Methodology has been refined


Photovoltaic Capacity Valuation Methods[edit | edit source]

Perez R. PHOTOVOLTAIC CAPACITY VALUATION METHODS.

There is a need to accurately determine the capacity value of Photovoltaic as more and more solar power is being installed. This paper presents different methods to find the capacity value of photovoltaic. There must be a consensus among the solar stake holders, the government and the research community as to which is the most appropriate method for capacity calculation of PV. Maintaining adequate generating capacity to meet electricity demand at all times is a fundamental principle for the electric utility industry. This is accomplished through a variety of means including providing/purchasing sufficient generation capacity as well as acquiring the associated ancillary services for the electricity grid.

PV CAPACITY VALUATION METHODS

  • Effective Load Carrying Capability (ELCC)
  • Load Duration Magnitude Capacity (LDMC)
  • Load Duration Time-based Capacity (LDTC)
  • Solar-Load-Control-Based Capacity (SLC)
  • Minimum-Buffer-Energy-Storage-based Capacity (MBESC)
  • Demand-Time Interval Matching (DTIM)
  • Time/Season Windows (TSW)
  • Capacity Factor (CF)

Three utilities Nevada Power (NP), Rochester Gas and Electric (RG&E), Portland General (PG) were selected for case studies to determine the best methods to find the capacity value.

From the study and by building general consensus three methods were identified as more preferable – Effective Load Carrying Capacity, Solar Load Control / Minimum Buffer Energy Storage (combined as one due to similarities), and Demand Time Interval Matching.

Spain’s Solar Market Crash Offers a Cautionary Tale About Feed-In Tariffs[edit | edit source]

Voosen, P. (2009). “Spain’s Solar Market Crash Offers a Cautionary Tale About Feed-In Tariffs.” New York Times.

This article briefly describes how wrong policy making can crash a market. Policies must always be implemented keeping the long time future in mind. Planning keeping only the near future in mind can lead to disaster as it happened in Spain's solar market.

The Spanish government adopted an aggressive policy by setting high renewable requirements and decided to give high subsidies to customers cooperating. This was keeping in mind that the south western part of Spain was a very good place for solar investments. the huge subsidies lead to a lot of solar panels being installed, such the the market crashed. Hence the government was forced to revise the faulty subsidy policy called the Feed in tariff, but by this time the damage had been done.The feed-in tariff established by Spain in 2007 guaranteed fixed electricity rates of up to 44 euro cents per kilowatt-hour to all new solar panel projects plugged into the electrical grid by September 2008. Also, a loophole in the tariff allowed bundles of small, ground-based projects to receive up to 575 percent of the average electricity price.

The photovoltaic market has been cutting its costs rapidly, and the Spanish tariff, with its high rates, created an artificial market, and this was the main cause of the crash. It costs more than 20,000 jobs and also the cost of panels came down due to excessive supply.

Ratemaking, Solar Value and Solar Net Energy Metering—A Primer[edit | edit source]

Cliburn, J.; Bourg, J.; Deffner, D.; Mahrer, E.; Sterling, J.; Taylor, M. (2013). “Ratemaking, Solar Value and Solar Net Energy Metering—A Primer.” Solar Electric Power Association.

This report initially goes into the details of how policy making is done in a government organization. The policy discussed here is ratemaking and to be specific the net metering policy. A lot of things must be taken into account when a ratemaking policy is developed. The primary rate-setting tools include

  • Customer Charge- The customer charge is that portion of the monthly customer bill that is “flat” and does not vary by the customer’s energy consumption or level of demand in a month. It is sometimes known as the basic charge or service fee
  • Volumetric Energy Charges- The volumetric energy charge is a rate per energy unit ($/kWh) that is designed to collect the energy-related costs incurred by a utility
  • Demand Charge and Power Factor- A demand charge collects the demand-related costs of the utility caused by the pattern of a customer’s energy usage. These costs include portions of the capacity cost of power plants, and portions of transmission, distribution and other infrastructure costs
  • Other rates and charges- Utilities may use many other rates to accomplish customer price signals and revenue recovery

The last part of the report describes the valuation of solar. The Net metering tariff mechanisism provides a good incentive to distributed generation customers.

State Clean Energy Practices: Renewable Energy Rebates[edit | edit source]

Lantz E, Doris E. State clean energy practices: renewable energy rebates. National Renewable Energy Laboratory; 2009 Mar 1.

Rebate programs have played a significant role in the emergence of distributed generation renewable energy markets and are likely to continue to play a critical role in the deployment and diffusion of renewables.

The most active and consistently successful renewable energy rebate programs often target photovoltaic (PV) technology. Historically, these programs have been a primary driver of market growth in this industry, resulting in thousands of solar power installations. The impact these rebates have on the PV markets in California, New Jersey and Colorado Oregon are also shown.

The success of prominent state rebate programs in stimulating PV installations is clear, however, it is less clear if these programs have effectively driven down PV technology costs. Some evidence shows that California’s installation costs and the balance of plant costs have declined (Wiser 2006). However, PV technology ultimately remains a niche technology out of reach for most potential consumers in the absence of continued rebates or other incentives



Physical and Economic Effects of Distributed PV Generation on California’s Distribution System[edit | edit source]

Cohen MA, Callaway DS. Physical Effects of Distributed PV Generation on California's Distribution System. arXiv preprint arXiv:1506.06643. 2015 Jun 18.

Key Findings

A comprehensive study was done and it was determined that

  • The energy value of PV is much higher than any economic effect it has on the distribution grid
  • The capacity investment deferral benefit appears to be smaller but potentially meaningful
  • Other effects were very low comparatively

Summary

  • It is justified to value PV at a higher rate than the retail rate
  • Compared to the wholesale cost of energy, PV's advantage is very small. Hence it is not justified to value PV at the full retail rate
  • More studies need to be conducted to accurately estimate the value of PV


  • The NREL on its analysis says 36% to 70% can be the ELCC for solar in various locations. Once the ELCC is chosen tge value of solar energy in avoiding the need for peak generation is simple. The cost of installing a simple cycle gas turbine is 475$ pe KW then the annual capital cost of peaking plant can be determined by multiplying this cost by capital recovery factor. These cost can then be converted inot per KW hr by dividing them by the hours of operation.
  • Developing sufficient solar to avoid peaking power plant not only avoids the cost of building the plant but also fixed and maintenance costs are avoided.
  • The cost of electricity per KWh can be determined using the heat rate or thermal efficiency of the power plant that is burning natural gas to produce electricity.

Capacity Value of Solar Power[edit | edit source]

Capacity value of solar power

  • Capacity value is used to quantify the contribution of renewable generators within generation adequacy, i.e. how much of conventional generation can be replaced by a renewable generator.
  • What is effective load carrying capability?: ELCC is any additional demand that the system may support at any given point of time. It is most commonly used to measure capacity.
  • Another commonly used generation adequacy index is loss of load expectation. It is the sum over time periods of loss of load probabilities. It is calculated over a year or more.
  • The most common LOLE calculation method is hind cast where the empirical historic time series demand and renewable capacity is used in the calculation as the joint distribution of demand and available renewable capacity.
  • Calculations are based on only the peak hour of each day. To reduce the computational burden weekends are excluded. But now with the advance computing the hourly LOLP is possible.
  • All the existing methodologies fall into following categories:
  1. Load duration curve is the mean relative PV output for all loads greater than a peak load L, minus the installed PV capacity X and p is the PV penetration factor p=X/L.
  2. DTIM is simply the reduction in demand when PV is added over a given evaluation period.
  3. SLC is used to determine how much more load reduction can be possible when demand response is available by deploying PV. SLC=(X-Y)/X where Y is amount of load reduction in absence of PV .
  4. MBESC determines the minimum buffer energy storage needed to guarantee firm peak reduction rather than cumulative demand response requirements.
  5. TSW is the mean output over selected peak demand periods to estimate the capacity value of renewable generators. This method is also called ERCOT method. Here there is no way of capturing the grid penetration levels and loads outside selected time window.


  • Citation:

Duignan, R., C. J. Dent, A. Mills, N. Samaan, M. Milligan, A. Keane, and M. O’Malley. "Capacity Value of Solar Power." In 2012 IEEE Power and Energy Society General Meeting, 1–6. San Diego, CA: IEEE, 2012. https://doi.org/10.1109/PESGM.2012.6345429.

  • Abstract

Evaluating the capacity value of renewable energy sources can pose significant challenges due to their variable and uncertain nature. In this paper the capacity value of solar power is investigated. Solar capacity value metrics and their associated calculation methodologies are reviewed and several solar capacity studies are summarized. The differences between wind and solar power are examined, the economic importance of solar capacity value is discussed and other assessments and recommendations are presented.

Avoidable Transmission Cost is a Substantial Benefit of Solar PV[edit | edit source]

Avoidable transmission cost is a substantial benefit of solar pv

  • This paper discusses how San Diego's proposed construction of 500KV transmission line known as sunrise project can be avoided.
  • Solar PV can defer the need for any additional large scale transmission. Deferral period by Borenstein's analysis is 25 years.
  • The first step in calculating the avoided cost would be to estimate how much transmission capacity is displaced.
  • Considering all the losses due to conversion from AC to DC a 10KW DC system would produce no more than 8.4KW AC which is Borenstein's estimation.
  • The transmission cost can increase when low capacity factor generation such as wind and solar requires new lines .
  • Solar PV is sufficiently large scale that can avoid expensive incremental transmission because it can be located at the load center.

The value of solar: prices and output from distributed photovoltaic generation in South Australia[edit | edit source]

The value of solar: prices and output from distributed photovoltaic generation in South Australia

  • The Australian government's Solar Cities program sees great value in pricing solar installations at pool prices. The purpose of this paper is to test the truth of that hypothesis.
  • An analysis of PV generation is first carried out across a typical year in South Adelaide, Australia and hourly, daily and annual values for PV generation are calculated.
  • Two different sets of prices are considered - one being the price small-end users would pay if an equivalent amount of energy was to be bought from the network which essentially amounts to the avoided cost of energy and the second by using hourly pool prices at which the end user might sell the electricity back to the network as it is generated.
  • The contract prices are set by the electric utilities by buying power in a wholesale fashion so as to cover all related costs across the regulated period.
  • Three different days were selected for detailed analysis - one being a hot summer's day with the transmission network heavily stressed, an unremarkable summer's day and a winter's day.
  • A comparison is made as to which value of pricing solar generates more value monetarily, the standing long-term contract price or the spot price.
  • The total value of solar generation was found to be around $550 for one whole year at the contract price whereas using the pool price yielded around only $93.
  • During the whole year, only about 19 days were found where using the pool price would lead to increased value of solar when compared to the contract price.
  • An argument is made by providing analysis as back-up that valuing solar at pool prices would simply be insufficient to encourage widespread adoption of PV.
  • Three scenarios are suggested which might lead to users being encouraged to adopt PV.
  • The first scenario being the energy of price goes up significantly which might lead to provision of better incentives for adoption of solar.
  • The second being an increase in pool prices that happens naturally due to a chronically stressed network and generating constraints.
  • The third being imposition of carbon taxes might also encourage solar adoption.
  • The above three scenarios might help create a scenario in which valuing solar at pool prices would be advantageous.

Value of PV energy in Germany benefit from the substitution of conventional power plants and local power generation[edit | edit source]

Value of PV energy in Germany benefit from the substitution of conventional power plants and local power generation

  • This paper is a detailed assessment of the value of PV energy within the German energy supply structure considering the co relation of PV with actual consumption and local power generation.
  • An evaluation is carried out for the year 2005 as well as a scenario in 2015.
  • For the purposes of this study, two important points have been considered - the PV's potential to replace conventional electric generation and the potential of decentralised energy generation to save costs in grid operation.
  • Based on irradiation and temperature data, time series of standardized PV power generation are computed for 120 locations.
  • A parameterized transforming algorithm is used to extrapolate PV power generation of various sites.
  • The algorithm uses two types of entry parameters - the standardized PV power generation for the respective sites and the spatial distribution of installed PV capacity.
  • The benefit of substitution of conventional electric generation is investigated by considering four different beneficial components :
  1. avoided variable power generation costs of the conventional sources
  2. avoided damage costs of CO2 emissions
  3. avoided fixed generation costs of the conventional generation infrastructure
  4. additional balancing costs caused by variations of PV power generation.
  • Decentralized PV generation systems have the potential to provide the following benefits:
  1. Reduction of network losses
  2. Reduction in network loading
  3. Improvement in quality, security and efficiency
  • A value of solar tariff is formulated according to the prices of 2005 which take into account all the benefits provided to the system as well as to the environment by using solar to replace conventional sources of energy.
  • An alternative approach is also suggested termed as the grid parity approach.
  • This approach calculates the grid parity, meaning the date, when generation costs or feed-in tariffs are below private power purchase tariffs. From the date of grid-parity the use of generated

PV energy will be more economic than its feed-in.

Realistic generation cost of solar photovoltaic electricity[edit | edit source]

Realistic generation cost of solar photovoltaic electricity

  • This paper formulates a way of calculating a realistic cost of solar energy rather than using the static grid price of electricity and in the process, come up with a new loan repayment scheme.
  • A change in solar loan policy is proposed by extending the loan repayment period in order to reflect the accurate value of solar energy instead of using conventional energy prices to determine the loan payback period and the installment amount.
  • The generation cost of SPV electricity in a given year is equal to the installment of loan repayment in that year divided by the annual number of units (kWh) of electricity generated. Most common method of loan repayment is the equated payment method. With this method the annual loan payment for each year during long loan payment period of 20–30 years remains same resulting in levelized generation cost for SPV electricity.
  • The rated capacity of solar photovoltaic (SPV) system for power generation in kWp is the electric output of SPV panels under standard conditions. Solar photovoltaic system of a given rated capacity installed at different places gives different amount of annual electric output (kWh/year).
  • The specific electric output of a system is introduced to take this variation into consideration. The specific electric output is the annual electric output of SPV system at a given place per unit rated capacity of the system.
  • The first step in the calculation of generation cost of solar PV electricity is to calculate the specific initial investment (Cs) of solar photovoltaic (SPV) power plant for different values of specific electric output and price of SPV power plant per unit rated capacity.
  • The curve obtained by plotting specific electric output against specific initial investment can be used to determine the value of specific initial investment required to install SPV system capable of generating one unit of electricity per year.
  • The value of specific initial investment helps to determine the initial investment required to generate given amount of electricity at a given place. Also it can be used to compare the initial investment required for SPV systems with different types of solar cells.
  • The second step is to determine the values of generalized capital recovery factor for different loan conditions. The generalized capital recovery factor accounts for factors relating to cost of financing i.e. loan interest rate, escalation in annual loan payments and loan period.
  • Finally, the generation cost of SPV electricity in the base year is calculated for different values of generalized capital recovery factor and specific initial investment of solar PV system.
  • Obviously, the SPV electricity becomes free of cost after the loan period till the end of working life of the system. The longer the period of unaccounted free electricity higher will be the cost of SPV electricity. Ideally the loan period needs to be equal to the working life of SPV system.
  • Hence, the loan period may be extended as close to the working life as possible to arrive at the realistic cost of SPV electricity to avoid unaccounted free electricity after the loan period.

Solar feed-in tariffs: Setting a fair and reasonable value for electricity generated by small-scale solar PV units in NSW[edit | edit source]

Solar feed-in tariffs: Setting a fair and reasonable value for electricity generated by small-scale solar PV units in NSW

  • This document is a commentary made by Origin Energy Limited on the solar feed-in tariffs issues paper released by the Independent Pricing and Regulatory Tribunal (IPART).
  • Origin believes in fixing the Feed-in Tariff (FIT) through competition between retailers.
  • Origin suggests two methods to calculate FIT.
  • The first is by estimating financial gain to the retailer.This consists of avoided spot prices due to PV users generating and selling energy back to the grid. To accurately calculate this, Origin proposes taking a close look at the following factors:
  1. The first-tier retailer’s settlement volume is measured as the residual of transmission node (TNI) demand once interval metered and profiled second-tier loads are subtracted from the total TNI load. The benefit is therefore difficult to measure with any accuracy, since no counterfactual spot price is available to reference.
  2. Different retailers will have a range of hedging strategies in place. A lower spot price may not be of benefit to a retailer with significant proportion of its load already hedged.
  3. The embedded generation output from a first tier retailer’s customers is not accounted for at settlement. However, the generation to the grid would have reduced the spot market price for all retailers (first and second tier) within a particular TNI. The first tier retailer is unable to fully capture this benefit and is not compensated for it by its second tier competitors.
  • The second method is by estimating the wholesale market value of the electricity which necessitates analyzing the factors below :
  1. The market value of solar PV should reflect the contribution made at various times of the day.
  2. The availability of solar PV, its predictability and certainty in forecasting when this contribution can take place may discount any value determined in the point above.
  3. Retailers have different hedging strategies and may value the contribution of solar PV (or any embedded generation) quite differently. Any market value determined needs to account for these scenarios.
  4. A value determined following these considerations might be compared with current voluntary FITs offered by retailers at present and if found to be similar, the case for intervention would not be required.
  • Origin concludes by stating that an FIT tariff fixed based on the competition between retailers would be the best way to fix a fair FIT for all parties involved.

An assessment of Thailand’s feed-in tariff program[edit | edit source]

An assessment of Thailand’s feed-in tariff program

  • This paper provides an assessment of Thailand's FIT program which is the most widely used national renewable energy policy worldwide.
  • The FIT program in Thailand is called Adder because it adds additional payment to renewable energy generators on top of normal prices that producers receive when they sell electricity to the electric utilities.
  • A major impediment to Thailand’s renewable energy development has been the lack of integration of renewable energy plans with Thailand’s long-term energy planning process.The most immediate manifestation of this policy ambivalence has been discontinuous support for the Adder measure, which e when operational eis one of the major mechanisms that will help the country meet its renewable energy targets. Discontinuous support for the Adder, in turn, has created a high level of uncertainty for investors.
  • The Adder program incentivizes renewable energy by guaranteeing attractive power purchasing rates.
  • The paper describes in detail the following facets of the Adder program : eligibility, rate structure, rates, cost control mechanism, approval process and criteria, contract term, support period, financing mechanism and program review.
  • There are four fundamental approaches for FIT rate determination in Thailand, which are as follows :
  1. Actual levelized cost of electricity
  2. The “value” of renewable energy generation, either to society or to the utility (the avoided cost of utility)
  3. Fixed-price incentives that are unrelated to the actual levelized cost of electricity generation or the value of renewable energy generation
  4. The result of an auction or bidding process
  • The development of the Adder program is described, which happened in three phases. In the first phase, the rules and regulations were streamlined and simplified. In the second phase, a bid bond, or

security deposit, of about $6/kW was introduced in reaction to high interest in applications in the first phase. The third phase of the Adder program can be characterized by frequent rule changing.

  • To summarize, the strengths of Thailand’s Adder program lie in rates that have been set high enough to attract private investment in diverse forms of renewable energy and in its early framework for streamlined interconnection arrangements and standardized documents including Power Purchase Agreements.
  • The paper concludes that Thailand has the foundations for a good feed-in tariff program but changes enacted after June 2010 (during phase 3) have slowed down market expansion.
  • It also concludes that the Adder program can be strengthened by focusing on planning, strategy, policy and regulatory framework for FIT.

Development of an economical model to determine an appropriate feed-in tariff for grid-connected solar PV electricity in all states of Australia[edit | edit source]

Development of an economical model to determine an appropriate feed-in tariff for grid-connected solar PV electricity in all states of Australia'

  • This paper describes the formulation of an economical model and a computer simulation to determine the accurate unit price of grid-connected roof-top solar photovoltaic (PV) electricity for all the states of Australia.
  • Sun data produced by the Australian Bureau of Meteorology has been used to produce accurate results.
  • Three radiation states are considered for each state and a rate is calculated for each state, after considering the perks provided by the government to consumers installing PV.
  • Rates are calculated for two possibilities -in which financial support is provided by the government and a case in which it is not.
  • In conclusion, the paper presents FIT for the state of Victoria and compares it to the cost consumers currently pay.
  • It also recommends that there should not be a uniform FIT throughout the country as radiation levels are different in different geographical locations.
  • It also concludes that the financial sops provided by the government need to be in accordance with a specific place's geographic location.

Distributed generation and distribution pricing: Why do we need new tariff design methodologies?[edit | edit source]

Distributed generation and distribution pricing: Why do we need new tariff design methodologies?

  • This paper presents a systematic review of the different challenges posed by an increasing amount of distributed generation within the distribution tariff design.
  • It reviews different distribution tariff options for distributed generation in different countries.
  • A review of the most relevant methodologies proposed in the literature to include distributed generation into the tariff design is also presented.
  • Recommendations on how to address the open issues with respect to tariff design and distributed generation are then presented in conclusion.

The economic effect of electricity net-metering with solar PV: Consequences for network cost recovery, cross subsidies and policy objectives[edit | edit source]

The economic effect of electricity net-metering with solar PV: Consequences for network cost recovery, cross subsidies and policy objectives

  • The increasing number of prosumers(consumers that both produce and consume electricity) with solar photovoltaic (PV) generation combined with net-metering results in reduced incomes for many network utilities worldwide. Consequently, this pushes utilities to increase charges per kW h in order to recover costs.
  • For non-PV owners, this could result into inequality issues due to the fact that also non-PV owners have to pay higher chargers for their electricity consumed to make up for netted costs of PV-owners.
  • In order to provide insight in those inequality issues caused by net-metering, this study presents the effects on cross-subsidies, cost recovery and policy objectives evolving from different applied net metering and tariff designs for a residential consumer.
  • Eventually this paper provides recommendations regarding tariffs and metering that will result in more explicit incentives for PV, instead of the current implicit incentives which are present to PV owners due to net-metering.
  • Net-metering presents an important dilemma between incentivizing distributed generation (DG) on one side and securing financial stability of the Distribution System Operator(DSO)on the other.
  • This paper has presented a study to provide insight into the dynamics that result from different types of net-metering methods and the impact on DSO incomes,policy objectives and increasing cross subsidies between network users.This study has been carried out using hourly consumption and production data for a low voltage network user in Spain with a Madrid based photovoltaic (PV) panel of 2 kWp capacity.

Overall review of renewable energy tariff policy in China: Evolution, implementation, problems and countermeasures[edit | edit source]

Overall review of renewable energy tariff policy in China: Evolution, implementation, problems and countermeasures

  • This paper introduces the current development situation of renewable energy, analyzes the evolution and implementation effect of the renewable energy tariff policy and discusses the problems of the renewable energy tariff policy in China. On this basis,this article has proposed feasibility tariff policy recommendations to solve the problems.
  • China's total energy supply from renewable energy demonstrated an average annual growth rate of about 12% between 2000 and 2010 and substituted 293 million t of coal equivalents by the end of that period. This necessitated a proper tariff structure in order to make sure renewable energy was properly valued.
  • The “Solar power development in the 12th Five-Year Plan” clearly defines the specific objectives of solar photovoltaic for the future. The solar power capacity will reach more than 21 million kW and the annual generation capacity will achieve 25 billion kW by 2015,including 10 million kW of total installed capacity of distributed photovoltaic power generation,10 million kW of total installed capacity of grid connected photovoltaic power generation capacity and 1 million kW of total installed capacity of solar thermal power.
  • Tariffs of solar power in China have experienced four stages: approval tariff stage, bidding price stage and fixed price stage.
  • The lack of necessary supporting policies in the valuation of solar power leads to bidding wars among private entities which leads to a serious deviation from the actual cost.
  • With the limitations of solar resources,the investment recovery period of solar power generation projects in eastern China is longer compared with western China,which hinders the development of photovoltaic power generation in that region.
  • The authors state that policy-makers need to refine attractive pricing policies and adjust the price at any time based on the changes of the cost of power generation.

Assessment of the minimum value of photovoltaic electricity in Italy[edit | edit source]

Assessment of the minimum value of photovoltaic electricity in Italy

  • This paper aims to assess the value of photovoltaic electricity in Italy, which is considered as an economically viable energy source in the medium and long term. A unique national hourly wholesale electricity price (PUN) is formed on the day-ahead market starting from the separate prices formed in several interconnected zones.
  • The analysis has been limited to the so called “peakhours,” that is, 8 AM to 8 PM CET during the workingdays around the year, while neither weekends nor national holidays were included due to the much lower power demand which, by means of the usual merit order mechanism, leads to the PUN formation quite similar to night time, therefore adding inhomogeneity to the analysis.
  • A multivariate regression model was chosen for the peak PUN series due to its simplicity, repeatability, stability,and successful use in related studies.
  • The values found by the authors is in line with related studies of near mature renewable energy markets.

The impacts of commercial electric utility rate structure elements on the economics of photovoltaic systems[edit | edit source]

The impacts of commercial electric utility rate structure elements on the economics of photovoltaic systems

  • This analysis uses simulated building data, simulated solar photovoltaic (PV) data, and actual electric utility tariff data from 25 cities to understand better the impacts of different commercial rate structures on the value of solar PV systems. By analyzing and comparing 55 unique rate structures across the United States, this study seeks to identify the rate components that have the greatest effect on the value of PV systems.
  • PVrate which is an MS-Excel based tool uses 15-minute or hourly data on building load and system production, as well as energy and demand charge information from a utility tariff sheet (usually available either online or by request). The building load data are chronologically aligned with the PV production data to determine the reduction in demand for each time segment. The tool then matches each time segment to the electricity rate that is applicable during that time to determine the energy and demand charges. The tool summarizes the energy, demand, and cost savings for each time segment, allowing for the identification of the beneficial components in each rate structure with regard to the PV system.
  • The load profile data used in this analysis were initially created in part for the DOE commercial building benchmark models (Torcellini et al. 2008) simulated using the EnergyPlus simulation software.
  • The PV production data used in this analysis were simulated using the typical meteorological year 28 (TMY2) dataset of the National Solar Radiation Database (NSRDB) (Marion and Urban 1995).
  • The primary metric used in this analysis is the PV savings metric, defined as the fraction of the annual electricity cost saved by the PV system:

PV savings = (electric bill without PV – electric bill with PV)/(electric bill without PV)*100%.

  • Common rate structure elements that appear to increase the value of PV include:
  1. TOU tariffs with peak pricing that is well correlated with PV production
  2. TOU tariffs that have a wide range between off-peak prices and peak prices
  3. Seasonal flat tariffs that have a relatively higher price in the summer than winter
  • Alternately, tariffs with demand charges tend to decrease the value of PV production. It was shown that PV systems, on average, have a relatively low capacity value, making them less attractive under rates with heavy demand charges.
  • The results also indicate that although TOU rates are generally more beneficial to buildings with PV systems, some TOU rates are less beneficial than others are due to undesirable correlation between peak pricing and PV production.

Strategies to mitigate declines in the economic value of wind and solar at high penetration in California[edit | edit source]

Strategies to mitigate declines in the economic value of wind and solar at high penetration in California

  • This paper evaluates several options to stem the decline of solar and PV energy value.
  • The authors previously conducted a case study in California which concluded that the value of solar decreased when penetration increased.
  • The paper suggests that low-cost bulk energy storage systems are a way of stemming the decrease in PV energy values.

Renewable financial support systems and cost-effectiveness[edit | edit source]

Renewable financial support systems and cost-effectiveness

  • This paper analyses the performance of ‘market-based’ and ‘feed-in tariff’ systems of renewable energy procurement, and comments on the impact of different procurement systems on investment in renewable energy.
  • The author's main aim is to assess the effectiveness of the UK’s ‘Renewable Obligation’ (RO) in achieving two key objectives; first the cost effective deployment of renewable energy, and second, an effective partnership with business at both the trans-national level and at the local level. The ‘Renewables Obligation’ (RO) penalises electricity suppliers which do not meet their quota for supplying renewable electricity.
  • A comparison is made between FIT and a pan-European green electricity market in green electricity certificates.
  • The author also doubts if stances taken by the neo-liberal side, who support a green electricity market rather than FIT aren't rooted solely in neo-liberal utopia of a globalised market without examining and/or proposing proper supporting measures to make sure their ideological thoughts are implementable in practicality.
  • The article finds that FIT tariff used in Germany is more cost-effective than the British RO.
  • The author also finds through analysis that different geographical locations may require different pricing strategies to ensure wide-spread adoption of renewable energy.

Why are residential PV prices in Germany so much lower than in the United States?[edit | edit source]

Why are residential PV prices in Germany so much lower than in the United States?

  • This document presents an analysis of why PV prices in Germany are far lower than that in the United States.
  • The authors performed extensive existing literature review and empirical research with 2 surveys of German residential PV installers.
  • The authors state that their analysis is only meant as a "first cut" and that further analysis in the pin-pointed areas would lead to more specific results.
  • The probable reasons found in the analysis are as follows:
  1. “Value-based pricing” in the U.S. (e.g., associated with more generous subsidies and/or less competition among installers)
  2. Preference for premium products in the U.S.
  3. Lower customer-acquisition costs in Germany due to simpler/more certain value proposition (FiT), critical mass of demand, and economies of scale
  4. Lower installation labor costs in Germany due to greater experience and economies of scale
  5. Lower permitting costs in Germany due to fewer requirements and greater standardization
  6. Less onerous electrical requirements and interconnection processes in Germany
  • A few measures were suggested to reduce PV prices in the United States, which are as listed below:
  1. A large and durable market size
  2. A concentrated market (which would minimize fragmentation)
  3. A simple, transparent, certain incentive structure / value proposition
  4. Simple interconnection, permitting, and inspection requirements
  5. Regular incentive declines to drive & follow cost reduction

A few suggested research areas have also been outlined in this document which could lead to a better understanding of the topic:

  1. Initiate a more refined analysis of overhead costs and margins among installers
  2. Better understand the pricing decision of installers and competition between installers (i.e., degree of “value-based pricing”)
  3. Further investigate installation practices and differing regulatory requirements (usage of grounding, roof-penetration and conduits)
  4. Compare supply-chain margins between the two countries and average prices paid by installers for modules and inverters
  5. Assess the role of FIT policies in Germany in stimulating price reductions and potential implications for U.S. solar policy

Valuation of Distributed Solar: A Qualitative View[edit | edit source]

Valuation of Distributed Solar: A Qualitative View

  • This paper assesses the value of distributed generation (DG) and to evaluate if the pricing policies being adopted are pushing the development of DG in an equitable direction.
  • It states that net metering for residential users leads to cross subsidies which are unfair.
  • Net metering also lets DG users get away with not paying their fair share of transmission fees despite using conventional grid energy when solar energy is not readily available.
  • Net metering is termed as being unfair and not reflective of the true cost of solar power.
  • It proposes the following criteria must be taken into account for coming up with a Value of Solar tariff :
  1. Capacity value
  2. Availability and reliability
  3. Solar DG does not avoid transmission costs
  4. Solar DG does not avoid distribution costs
  • It concludes by opining that solar DG is a very valuable resource but if it is not properly priced taking into account its ill-effects as well as advantages, then it would be counterproductive to solar DG in the future.

The Value of Solar tariff: Net Metering 2.0[edit | edit source]

The Value of Solar tariff: Net Metering 2.0

  • This paper strongly endorses the need for adopting the Value of Solar Tariff (VOST) in order to encourage more and more solar to be installed.
  • The author notes three points which would be the hallmark of an ideal tariff system, which are :
  1. A distributed solar tariff should be fair to the utility and to non-solar customers
  2. The ideal solar tariff should fairly compensate the solar customer
  3. The tariff should recover costs and give compensation credit for value independently from an incentive designed to overcome market failures
  4. An ideal distributed solar tariff would operate as a complement to other electricity policy goals, including, especially, a goal of more efficient use of energy
  5. An ideal distributed solar tariff should be intuitively sound and administratively simple to implement and manage
  • Although net metering is described as a breakthrough in energy policy at that time, it has its own drawbacks.
  • The VOST tariff structure formulated by Austin Energy is praised as a good example of a solar tariff structure which tries to accommodate all concerned factors.

A Rising Tension: ‘Value-of-Solar’ Tariff Versus Net Metering[edit | edit source]

A Rising Tension: ‘Value-of-Solar’ Tariff Versus Net Metering

  • This article details the conflict between two groups with regards to which tariff system is better, net metering or Value of Solar Tariff (VOST).
  • The Alliance for Solar Choice (TASC), which is made up of leading solar service providers, is a staunch supporter of net metering.
  • It believes that net metering is a stable and highly successful policy and that it needs to be maintained and not fixed.
  • Electric utilities feel net metering is unfair as it shifts the transmission infrastructure maintenance costs to non-solar users.
  • A VOST advocate defends VOST as having the following benefits:
  1. Avoiding the purchase of energy from other, polluting sources
  2. Avoiding the need to build additional power plant capacity to meet peak energy needs
  3. Providing energy for decades at a fixed price
  4. Reducing wear and tear on the electric grid, including power lines, substations, and power plants

Harnessing The Power Of The People Through "Value Of Solar"... And Beyond[edit | edit source]

Harnessing The Power Of The People Through "Value Of Solar"... And Beyond

  • This article details the brewing debate in various solar-leading countries over net metering versus value of solar tariff.
  • It advocates the need for utilities to give monetary credit to customer behavior which impacts the grid in a positive way.
  • It also supports assigning value to various distributed energy resources like energy efficiency, demand response or energy storage.
  • It opines that instead of waiting for the next clean energy fight to boil up, states should consider looking beyond the value of individual technologies, and redesign power rates to take advantage of diverse customer resources and energy innovations.

Value of Solar Methodology[edit | edit source]

Value of Solar Methodology

  • This document explains in detail a procedure to calculate the value of solar.
  • It has been formulated by Clean Power Research.
  • A different methodology has been proposed for Iowa, Michigan and Wisconsin.

A rational look at the value of solar[edit | edit source]

A rational look at the value of solar

  • This article stresses the importance of not blindly comparing VOS rates of different studies.
  • It asks for a rational outlook on the various factors that might be affecting the rates in these different methods.
  • Hence, VOS rates must not be compared strictly based on their exact monetary value and a holistic outlook is needed.
  • A case study is described which encompasses two VOS rates calculated by two different entities and in the process getting different results.
  • VOS value differences depend on the following factors - the analysis framework, the cost/benefit categories and the input assumptions.
  • Another case study conducted in Maine is presented which also reported a difference in VOS values.

In conclusion, the author feels it would be helpful to rationally assess the various VOS rates and then make a decision which would be in the best interests of the solar industry.

==A New “Sunshine State”?Evaluating Minnesota’s Value of Solar Tariff Methodology== A New “Sunshine State”?Evaluating Minnesota’s Value of Solar Tariff Methodology

  • This paper presents an evaluation of Minnesota's VOST methodology.
  • It details the importance of VOS and hails it as a necessary breakthrough in energy policy while going into detail about what factors the VOS takes into consideration.
  • It also identifies a few shortcomings in the VOS methodology.
  • The greatest shortcoming of Minnesota’s VOST methodology ironically stems from one of its most appealing characteristics.VOST purports to offer a rate between the utility’s avoided-cost and retail rates.Unfortunately,reports indicate that the VOST rate exceeds present retail rates for residential end users.
  • Another shortcoming identified is the VOST's inability to distinguish itself from Minnesota's existing net metering policy.
  • However, the author still feels that VOST can still be a very useful energy tool to value solar energy. It is a viable alternative to compensating customers at the utility’s avoided-cost rate, and it would expressly account for the environmental benefits of solar, whereas an avoided-cost rate will not necessarily do so.


  • Citation

Miller, Addison O. “A New ‘Sunshine State’? Evaluating Minnesota’s Value of Solar Tariff Methodology.” ENVIRONMENTAL LAW 7, no. 2 (2016): 12.

Arizona regulators end retail net metering in value-of-solar proceeding[edit | edit source]

Arizona regulators end retail net metering in value-of-solar proceeding

  • This article details a legislative action in Arizona which ended net metering.
  • It will be replaced with a reduced rate of compensation for solar customers.
  • This step would actually reduce the compensation offered to solar customers by about 30%, according to representatives from Vote Solar and The Alliance for Solar Choice.
  • The solar advocates desired a compromise between net metering and VOS, but the judgment rendered that desire moot.


  • Citation

Utility Dive. “Updated: Arizona Regulators End Retail Net Metering in Value-of-Solar Proceeding.” Accessed January 27, 2020. https://www.utilitydive.com/news/updated-arizona-regulators-end-retail-net-metering-in-value-of-solar-proce/432838/.

Is A Value Of Solar Tariff (VOST) Really Better Than Net Metering?[edit | edit source]

Is A Value Of Solar Tariff (VOST) Really Better Than Net Metering

  • This article details the advantages of VOST but introduces a new perspective on evaluating tariffs - if it is good for the long term.

The author opines that VOS would be a short term move and hence net metering is the better alternative to ensure the continued growth of the solar industry.

A comparative assessment of net metering and feed in tariff schemes for residential PV systems[edit | edit source]

A comparative assessment of net metering and feed in tariff schemes for residential PV systems

  • Citation

Poullikkas, Andreas. “A Comparative Assessment of Net Metering and Feed in Tariff Schemes for Residential PV Systems.” Sustainable Energy Technologies and Assessments 3 (September 1, 2013): 1–8. https://doi.org/10.1016/j.seta.2013.04.001.

  • Abstract

In this work, a comparative assessment of net metering vs. feed-in-tariff (FiT) supporting schemes for residential PV systems is carried out. A formulation for the computation of net metering supporting scheme parameters, in half hour intervals, is developed and typical household integrated with a rooftop PV system is investigated. The effect of the size of PV system with respect to the net metering supporting scheme is examined by varying the PV capacity and the effect of the electricity retail cost rate is investigated by varying the electricity retail cost rate. The comparative results indicate that net metering supporting scheme performs better than a FiT supporting scheme when the household electricity bill is taken into account. From the analysis it is clear that under certain conditions net metering supporting scheme becomes profitable.

Key Takeaways
Misconceptions of Net Metering:
  1. Net Metering hurts utility production by decreasing revenues
  2. When using Net Metering, a group of user pays for another group of user
  3. Net metering is a burden for small utilities
Simulation of cost of rooftop PV system with different peak powers and different retailed electricity costs
Feed-in tariff (VOS / FIT) performs better than Net Metering
Net Metering only performs better that FIT in certain specific conditions

Valuation of Distributed Solar: A Qualitative View[edit | edit source]

Valuation of Distributed Solar: A Qualitative View

  • Citation

Brown, Ashley, and Jillian Bunyan. “Valuation of Distributed Solar: A Qualitative View.” The Electricity Journal 27, no. 10 (2014): 27–48. https://doi.org/10.1016/j.tej.2014.11.005.

  • Abstract

A critical evaluation of the arguments used by solar DG advocates shows that those arguments may often overvalue solar DG. It is time to reassess the value of solar DG from production to dispatch and to calibrate our pricing policies to make certain that our efforts are equitable and carrying us in the right direction.

Key Takeaways
Criticize the Net Metering approach
Emphasis on the inclusion of all relevant ones externalities when calculating value of solar and not cherry-picking for particular interest (Section III of report)
When non-economic objectives are to be factored into value,then it is wise to carefully consider the most economically efficient ways of attaining those objectives.

Endogenous Assessment of the Capacity Value of Solar PV in Generation Investment Planning Studies[edit | edit source]

Endogenous Assessment of the Capacity Value of Solar PV in Generation Investment Planning Studies

  • Citation

Munoz, Francisco D., and Andrew D. Mills. “Endogenous Assessment of the Capacity Value of Solar PV in Generation Investment Planning Studies.” IEEE Transactions on Sustainable Energy 6, no. 4 (October 1, 2015): 1574–85. https://doi.org/10.1109/tste.2015.2456019.

  • Abstract

There exist several different reliability-and approximation-based methods to determine the contribution of solar resources toward resource adequacy. However, most of these approaches require knowing in advance the installed capacities of both conventional and solar generators. This is a complication since generator capacities are actually decision variables in capacity planning studies. In this paper, we study the effect of time resolution and solar PV penetration using a planning model that accounts for the full distribution of generator outages and solar resource variability. We also describe a modification of a standard deterministic planning model that enforces a resource adequacy target through a reserve margin constraint. Our numerical experiments show that at least 50 days worth of data are necessary to approximate the results of the full-resolution model with a maximum error of 2.5% on costs and capacity. We also show that the amount of displaced capacity of conventional generation decreases rapidly as the penetration of solar PV increases. We find that using an exogenously defined and constant capacity value based on time-series data can yield relatively accurate results for small penetration levels. For higher penetration levels, the modified deterministic planning model better captures avoided costs and the decreasing value of solar PV.

Climate impacts on the cost of solar energy[edit | edit source]

Climate impacts on the cost of solar energy

  • Citation

Flowers, Mallory E., Matthew K. Smith, Ara W. Parsekian, Dmitriy S. Boyuk, Jenna K. McGrath, and Luke Yates. “Climate Impacts on the Cost of Solar Energy.” Energy Policy 94 (July 2016): 264–73. https://doi.org/10.1016/j.enpol.2016.04.018.

  • Abstract

Photovoltaic (PV) Levelized Cost of Energy (LCOE) estimates are widely utilized by decision makers to predict the long-term cost and benefits of solar PV installations, but fail to consider local climate, which impacts PV panel lifetime and performance. Specific types of solar PV panels are known to respond to climate factors differently. Mono-, poly-, and amorphous-silicon (Si) PV technologies are known to exhibit varying degradation rates and instantaneous power losses as a function of operating temperature, humidity, thermal cycling, and panel soiling. We formulate an extended LCOE calculation, which considers PV module performance and lifespan as a function of local climate. The LCOE is then calculated for crystalline and amorphous Si PV technologies across several climates. Finally, we assess the impact of various policy incentives on reducing the firm's cost of solar deployment when controlling for climate. This assessment is the first to quantify tradeoffs between technologies, geographies, and policies in a unified manner. Results suggest crystalline Si solar panels as the most promising candidate for commercial-scale PV systems due to their low degradation rates compared to amorphous technologies. Across technologies, we note the strong ability of investment subsidies in removing uncertainty and reducing the LCOE, compared to production incentives.

Key Takeaways
Previous calculations of Levelized Cost of Solar in literature do not account for climate effects system lifetime
Local weather conditions impact the performance of panels according to the manufacturing technology.
Development of new cost analysis method where panel lifetime equals lifetime to reach 80% of initial performance
Method account for ambient temperature effect on PV system
Method do not include grid reliability, averted emissions or environmental impacts

MIT Energy Initiative - Utility of the future[edit | edit source]

MIT Energy Initiative - Utility of the future

  • Citation

“Utility of the Future.” MIT Energy Initiative. MIT, December 2016. http://energy.mit.edu/wp-content/uploads/2016/12/Utility-of-the-Future-Full-Report.pdf.

Key Takeaways
Value of electricity depends on location of supply and demand
Description of locational and non-locational values content in Distributed Energy Resources (DERs)
Value of DERs depends on location of injection nodes:
  1. Constraints: line or transformer thermal capacity, node voltage, stability
  2. Losses: depends on location of the node
Value of DERs increases where constraints and losses are binding
DERs can sometime contribute to losses by production of reverse power-flow for low voltages (Check Schmalensee 2015 and Goop 2016)
Distributed Solar PV may have more locational value than Centralized plants
LCOE calculated for crystalline and amorphous technologies for different climate regions
Degradation rates collected from field studies data
Method can be applied to broad range of solar PV installations
Incomplete method: could be improve by including environmental impacts and other related costs.

Optimal Policies to Promote Efficient Distributed Generation of Electricity[edit | edit source]

Optimal Policies to Promote Efficient Distributed Generation of Electricity

  • Citation

Brown, David P., and David E. M. Sappington. “Optimal Policies to Promote Efficient Distributed Generation of Electricity.” Journal of Regulatory Economics 52, no. 2 (October 1, 2017): 159–88. https://doi.org/10.1007/s11149-017-9335-9.

  • Abstract

We analyze the design of policies to promote efficient distributed generation (DG) of electricity. The optimal policy varies with the set of instruments available to the regulator and with the prevailing DG production technology. DG capacity charges often play a valuable role in inducing optimal investment in DG capacity, allowing payments for DG production to induce the optimal production of electricity using non-intermittent DG technologies. Net metering can be optimal in certain settings, but often is not optimal, especially for non-intermittent DG technologies.

Key Take aways
Payments methods for DG technologies:
  1. Net Metering
  2. Value of Production (Value Of Solar in the cas of PV)
  3. Avoided Cost
Compensation Policies must be made according to the DG technology considered
Net metering can be optimal for intermittent DG technologies
Net metering is not optimal even for intermittent DG technologies when regulator is unable to set DG capacity charges.

Distributed rate design: A review of early approaches and practical considerations for value of solar tariffs[edit | edit source]

Distributed rate design: A review of early approaches and practical considerations for value of solar tariffs

  • Citation

Simshauser, Paul. “Distribution Network Prices and Solar PV: Resolving Rate Instability and Wealth Transfers through Demand Tariffs.” Energy Economics 54 (February 1, 2016): 108–22. https://doi.org/10.1016/j.eneco.2015.11.011.

  • Abstract

1-in-4 detached households in Southeast Queensland have installed rooftop solar PV—amongst the highest take-up rates in the world. Electricity distribution network capacity is primarily driven by periodic demand, and household load generally peaks in the early evening, whereas solar PV production peaks during the middle of the day and thus a mismatch exists. Compounding matters is the fact that the structure of the regulated two-part network tariff is dominated by a flat-rate variable charge. In this article, interval meter data at the customer switchboard circuit level confirms that solar households use only slightly less peak capacity than non-solar households and, that non-trivial cross-subsidies are rapidly emerging. A tariff model demonstrates that a peak capacity-based ‘demand tariff’ is a more efficient, cost-reflective and equitable pricing structure that improves the stability of tariffs given a rate-of-return regulatory constraint.

Key Takeaways
The purpose of the article is to identify a more efficient and stable ‘structure’ for network tariffs that accommodates solar PV and other distributed technology investments in a low growth environment, and for any given asset valuation.
Solar PV households consume dramatically less in lower value shoulder periods and because electricity tariffs are dominated by a flat-rate variable charge, they pay considerably less than non-solar households.
Residential customers in the Southeast Queensland distribution network are modeled using interval meter data at the customer switchboard circuit level for four typical household load types with and without air-conditioners, and with and without solar PV
Cost analysis in the article focuses on network charges
Consumer load data collected in houses at switchboard circuit level
Took into account the seasonal variation of the load
Proposition of a Three-Part Demand Tariff (comprising a fixed charge, a variable kWh charge, and a maximum kW demand charge) will produce a more efficient and more equitable price signal and will correct the incidence of ‘implicit subsidies’ that are rapidly emerging.
Unlike the Tariff Model contained in Simshauser and Downer (2015) which considered supply chain costs of generation, transmission, distribution and retail, in the present analysis only network tariffs are considered

Data Challenges in Estimating the Capacity Value of Solar Photovoltaics[edit | edit source]

Data Challenges in Estimating the Capacity Valueof Solar Photovoltaics

  • Citation

Gami, Dhruv, Ramteen Sioshansi, and Paul Denholm. “Data Challenges in Estimating the Capacity Value of Solar Photovoltaics.” IEEE Journal of Photovoltaics 7, no. 4 (July 2017): 1065–73. https://doi.org/10.1109/JPHOTOV.2017.2695328.

  • Abstract

We examine the robustness of solar capacity-value estimates to three important data issues. The first is the sensitivity to using hourly averaged as opposed to subhourly solar-insolation data. The second is the sensitivity to errors in recording and interpreting load data. The third is the sensitivity to using modeled as opposed to measured solar-insolation data. We demonstrate that capacity-value estimates of solar are sensitive to all three of these factors, with potentially large errors in the capacity-value estimate in a particular year. If multiple years of data are available, the biases introduced by using hourly averaged solar-insolation can be smoothed out. Multiple years of data will not necessarily address the other data-related issues that we examine. Our analysis calls into question the accuracy of a number of solar capacity-value estimates relying exclusively on modeled solar-insolation data that are reported in the literature (including our own previous works). Our analysis also suggests that multiple years’ historical data should be used for remunerating solar generators for their capacity value in organized wholesale electricity markets.

  • Key Takeaways
  1. Evaluation of PV capacity value estimation methods' robustness
  2. Impact of using hourly solar irradiation Data on the PV capacity value
  3. Impact of Day Light Savings on Load Data and PV capacity value
  4. Sensitivity of PV capacity value to measured data as opposed to simulated sata
  5. ELCC, increase of system load when solar is added to system without impact on reliability, is used as capacity value metric
  6. ELCC computing methods and steps
  7. 10 Locations case study with 1-min available data
  8. Use of estimated solar production data

The capacity value of optimal wind and solar portfolios[edit | edit source]

The capacity value of optimal wind and solar portfolios

  • Citation

Shahriari, Mehdi, and Seth Blumsack. “The Capacity Value of Optimal Wind and Solar Portfolios.” Energy 148 (April 1, 2018): 992–1005. https://doi.org/10.1016/j.energy.2017.12.121.

  • Abstract

Using large data sets of simulated wind and solar energy production, we create optimal wind, solar and blended (combined wind and solar) portfolios over various spatial and temporal scales, and use portfolio theory to quantify the capacity benefits in various portions of the electric grid in the Eastern United States. We add to the existing literature on portfolio analysis of renewable energy resources by (i) studying the benefits of optimal aggregation over various spatial and temporal scales, (ii) quantifying the capacity benefits of renewable portfolios over space and time, and (iii) analyzing spatial distributions of renewable installations in optimal renewable portfolios. The results indicate that full time availability of wind and blended portfolios are respectively 14 and 17 times larger than full time availability of an individual wind farm and adding solar to wind portfolios increases the availability factor of renewable portfolios by more than 40% in most regions. Further, optimal hourly portfolios provide higher capacity value relative to daily and weekly portfolios.

Key Takeaways
To fill in

Impacts of wind and solar spatial diversification on its market value: A case study of the Chilean electricity market[edit | edit source]

Impacts of wind and solar spatial diversification on its market value: A case study of the Chilean electricity market

  • Citation

Odeh, Rodrigo Pérez, and David Watts. “Impacts of Wind and Solar Spatial Diversification on Its Market Value: A Case Study of the Chilean Electricity Market.” Renewable and Sustainable Energy Reviews 111 (September 1, 2019): 442–61. https://doi.org/10.1016/j.rser.2019.01.015.

  • Abstract

Renewable energy is expected to become the main electricity source in the world in the coming decades, with solar and wind power taking a big share of the energy supply. Although there has been a remarkable advance on renewable energy technologies, their integration is still difficult for regulators, market designers and system operators due to the high variability and limited predictability of solar and wind resources. Measures can be adopted to ease their integration, among them geographical diversification. There is plenty of literature about the diversification of solar and wind resources and there is a common conclusion: greater dispersion smooths out power production. However, literature on the effects of spatial diversification on the power system, electricity prices and renewable energy market value is much scarcer. This paper studies the effects of spatial diversification and questions whether integration policies are incentivizing the placement of renewable generators where they provide the highest value to the electricity system in Chile. Using real data and a simplified dispatch model the analysis presented shows evidence of the effects of diversification on wind and solar market value in Chile. Results suggest that spatial diversification has a strong positive effect on the market value of renewable energy, especially in scenarios with active transmission and hydro-storage constraints. Wind market value may vary up to US$10/MW h depending on the level of diversification and the spatial and temporal constraints of the system and, given current storage capacity of hydro reservoirs, the solar market value may increase US$5/MW h due to diversification if transmission capacity is enough. Even though these results must be observed with caution, because they depend on the assumptions made, there is an important effect of renewable spatial diversification that should be observed by regulators.

Key Takeaways
This study shows the impact of transmission and storage constraints on wind and solar market value
The rapid grown of solar and wind power generation the last five years is expected to continue and eventually leave conventional sources behind
If more generators are installed in one location (seeking a good primary resource)the market value of that location decreases (due to the excess of supply)
Economic value of VRE: Revenue that generators earn on the market
Since electricity storage is expensive, production time greatly affects the value of electricity (given that demand and resources availability change over time)
Electricity value depends on location (Losses and transmission)
VRE market value depends strongly on the system and its conditions(such as the energy mix, grid topology, transmission capacity and distance to the consumption centers)
Flexibility is understood as the ability of a system to withstand changes in power demand and generation, and more flexibility helps power systems to adopt more renewable energy, but also to mitigate the reduction of the economic value of VRE with increasing penetrations levels.
VRE market value is impacted by its spatial diversification
As renewable penetration increases, its market value goes down, and it becomes more difficult to integrate them. One of the main effects when renewable energy increase its share is a price drop, known as the"merit-order effect".

Spatial and temporal variation in the value of solar power across United States electricity markets[edit | edit source]

Spatial and temporal variation in the value of solar power across United States electricity markets

  • Citation

Brown, Patrick R., and Francis M. O’Sullivan. “Spatial and Temporal Variation in the Value of Solar Power across United States Electricity Markets.” Renewable and Sustainable Energy Reviews 121 (April 1, 2020): 109594. https://doi.org/10.1016/j.rser.2019.109594.

  • Abstract

The cost of utility-scale photovoltaics (PV) has declined rapidly over the past decade. Yet increased renewable electricity generation, decreased natural gas prices, and deployment of emissions-control technology across the United States have led to concurrent changes in electricity prices and power system emissions rates, each of which influence the value of PV electricity. An ongoing assessment of the economic competitiveness of PV is therefore necessary as PV cost and value continue to evolve. Here, we use historical nodal electricity prices, capacity market prices, marginal power system emissions rates of CO2 and air pollutants, and weather data to model the energy, capacity, health, and climate value of PV electricity at over 10 000 locations across six U.S. Independent System Operators (ISOs) from 2010 to 2017. On the energy and capacity markets, transmission congestion in some locations and years results in PV revenues that are more than double the median across the relevant ISO. While the marginal public health benefits from avoided SO2, NOx, and PM2.5 emissions have declined over time in most ISOs, monetizing the health benefits of PV generation in 2017 would increase median PV energy revenues by 70% in MISO and NYISO and 100% in PJM. Given 2017 PV costs, electricity prices, and grid conditions, PV breaks even at 30% of modeled locations on the basis of energy, capacity, and health benefits, at 75% of modeled locations with the addition of a 50 $/ton CO2 price, and at 100% of modeled locations with a 100 $/ton CO2 price. These results suggest that PV cost decline has outpaced value decline over the past decade, such that in 2017 the net benefits of utility-scale PV outweigh the cost at the majority of modeled locations.

Key Takeaways
Focus on benefits provided by solar in terms of displaced energy, capacity, public health, and climate change from 2010 to 2017
“Merit-order effect” is most pronounced during times of day when solar energy generation is highest, causing the average market value of solar electricity to decline even more rapidly than the average electricity price
Simulation Used
  1. Historical data for solar irradiation from NSRDB
  2. PV Model in PVLIB Toolbox : PV orientation / inverter ration / system losses / module temperature losses
  3. Horizontal 1-axis tracking crystalline silicon
  4. Non-curtailable PV systems
  5. A companion analysis uses this dataset to explore the impact of temporal PV output shaping
Four components of PV gen value are modeled:
  1. Energy
  2. Resource adequacy
  3. Public Health benefits
  4. Climate Change mitigation
Data Sources:
  1. Meteorological data from NSRDB
  2. Electricity prices from ISO
  3. Marginal emissions and damages from Azevedo et al. and Siler-Evans et al. [17,48].
  4. PV Capacity: open PV project
Limitations
  1. Impact of explicit subsidies not included
  2. The value is only assess for a short fixed period of time, not for the medium or long-run
  3. Impact of solar forecasting not included
  4. GHG emissions have not been quantified using a life cycle analysis
  5. Monetized health and climate benefits are difficult to assess
  6. The presence of an emissions cap and trade program can complicate an assessment of the marginal emissions offset of solar
Sunniest places are not always the most suitable for solar
Data and computer codes available here

Future wind and solar power market values in Germany — Evidence of spatial and technological dependencies?[edit | edit source]

Future wind and solar power market values in Germany — Evidence of spatial and technological dependencies?

  • Citation

Eising, Manuel, Hannes Hobbie, and Dominik Möst. “Future Wind and Solar Power Market Values in Germany — Evidence of Spatial and Technological Dependencies?” Energy Economics 86 (February 1, 2020): 104638. https://doi.org/10.1016/j.eneco.2019.104638.

  • Abstract

Achieving ambitious climate targets entails an extensive utilization of renewable energy sources. However, due to weather-dependent fluctuations, generation from variable renewable energy (VRE) sources is characterized by significantly lower market values in comparison to conventional technologies, reinforced by a decline in electricity prices. This development poses interesting questions as to its drivers and to what extent market values of wind and solar power can be influenced by the design of electricity markets. Against this background, a scenario-based analysis is conducted to trace the future development of market values using endogenously derived electricity prices considering different regional and technological VRE diversification strategies and investments into VRE technologies on a myopic basis. The results show a continued decline in market values with increasing regional discrepancies indicating a growing importance of inter-regional inter-dependencies for assessing the profitability of VRE. Furthermore, from a system point of view, a more distributed allocation of onshore wind capacities to contend with declining market values does not always prove to stabilize market values by facilitating a more constant feed-in pattern, contrary to expectation. Finally, replacing onshore with offshore wind energy appears to be beneficial as it can lead to an overall increase in the market values of offshore, onshore as well as PV generation technologies compared to other mitigation strategies. This result raise interesting questions about the systemic economic value of offshore wind despite its higher LCOE in the context of market integration of VRE.

Key Takeaways
The paper aims at contributing to the extant literature by assessing the development of the market value and its drivers with a spatially dis-aggregated representation
The weather-dependent variability of VRE generation as well as varying demand and high storage costs affect daily and seasonal price patterns
From a welfare- theoretical perspective,the market value can be seen as the marginal social benefit of VRE generation.
From an investor’s perspective, the market value cor-responds to the specific market revenues (without subsidies) earned
The paper provides formulas to evaluate:
  1. The short-term market value of VRE
  2. The long-term market value of VRE
  3. The Value Factor of VRE
Explanation of "merit-order" effect: exogenous and endogenous drivers influence the value factor
Exogenous drivers:
  1. VRE market shares and feed-in pattern
  2. Storage and demand flexibility
  3. Fuel and CO2 prices
  4. Cross-border network expansion
  5. Power plant portfolios
  6. Market structure and market design
Endogenous drivers
  1. Technological diversity (TDiv)
  2. Technological design (TDes)
  3. Geographical diversity (GDiv)
Findings
  1. Technological composition and geographical distribution of VRE impact their cost
  2. PV value factor decreases significantly as VRE shares increase
  3. Geographical diversification does not necessarily counteract falling VRE value factor
  4. A geographically diverse generation portfolio was employed to level out the variability of the generation from VRE dueto a decreasing pair-correlation across distances
  5. When pursuing investments in VRE plants, it is important not only to consider current local market revenues in conjunction with site-specific LCOE but also the future development of regional market values

A geographically resolved method to estimate levelized power plant costs with environmental externalities[edit | edit source]

A geographically resolved method to estimate levelized power plant costs with environmental externalities

  • Citation

Rhodes, Joshua D., Carey King, Gürcan Gulen, Sheila M. Olmstead, James S. Dyer, Robert E. Hebner, Fred C. Beach, Thomas F. Edgar, and Michael E. Webber. “A Geographically Resolved Method to Estimate Levelized Power Plant Costs with Environmental Externalities.” Energy Policy 102 (March 1, 2017): 491–99. https://doi.org/10.1016/j.enpol.2016.12.025.

  • Abstract

In this analysis we developed and applied a geographically-resolved method to calculate the Levelized Cost of Electricity (LCOE) of new power plants on a county-by-county basis while including estimates of some environmental externalities. We calculated the LCOE for each county of the contiguous United States for 12 power plant technologies. The minimum LCOE option for each county varies based on local conditions, capital and fuel costs, environmental externalities, and resource availability. We considered ten scenarios that vary input assumptions. We present the results in a map format to facilitate comparisons by fuel, technology, and location. For our reference analysis, which includes a cost of $62/tCO2 for CO2 emissions natural gas combined cycle, wind, and nuclear are most often the lowest-LCOE option. While the average cost increases when internalizing the environmental externalities (carbon and air pollutants) is small for some technologies, the local cost differences are as high as $0.62/kWh for coal (under our reference analysis). These results display format, and online tools could serve as an educational tool for stakeholders when considering which technologies might or might not be a good fit for a given locality subject to system integration considerations.

Key Takeaways
LCOE typically only considers costs that are internal to the plant itself such as:
  1. Capital costs (CAPEX)
  2. Debt service costs
  3. Fixed Operations and Maintenance costs
  4. Variable O & M costs
  5. The heat rate
  6. The fuel cost
  7. The capacity factor
The study incorporates region-specific data on CAPEX, O & M, and fuel costs, where available, and uses geographical interpolation techniques to calculate them on a county-by-county basis in the United States.
Not considered in the study:
  1. Temporal fidelity
  2. Levelized avoided cost of electricity (LACE)
  3. The impact of subsidies
  4. And the ability to incorporate performance factors
Methods: The approach used in the paper is the conventional LCOE formulation to which environmental externalities are integrated, after which the calculations are executed with geographical differentiation.
Formula for calculations of LCOE are provided

Summaries of Recent State Actions on Net Energy Metering Policies in Five Vertically Integrated and Five Restructured States[edit | edit source]

  • Citation

Barber, Jamie, and Tom Stanton. “Summaries of Recent State Actions on Net Energy Metering Policies in Five Vertically Integrated and Five Restructured States,” n.d.

Key Takeaways
Georgia
  1. Discussion on VOS in play in the state of Georgia since 2014
  2. Georgia Power defined 21 separate elements of system costs that could change, up or down, when a renewable resource is added to the grid.
Hawaii
  1. One of the first states to end its net metering program and approve successor tariffs
  2. New DG tariffs: grid-supply tariff and customer self-supply (CSS) tariff
Minnesota
  1. VOS components: energy and its delivery; generation capacity; transmission capacity; transmission and distribution line losses; and environmental value.
DC Value Of Solar: On May 19, 2017, the DC Office of the People's Counsel (OPC) filed a value of solar study
New York: Value of Distributed energy Resources to replace Net Metering (Work in progress)

Review of State Net Energy Metering and Successor Rate Designs[edit | edit source]

  • Citation

Stanton T. Review of State Net Energy Metering and Successor Rate Designs. National Regulatory Research Institute; 2019.

  • Executive Summary

The objective of this paper is to summarize actions now being taken in many states to change rate designs for distributed energy resources (DER) on the customer side of the meter. Net energy metering (NEM) has been the most common rate design used for customers with small-scale generators that provide what is sometimes known as self-service power. Recently, there has been considerable interest in finding alternatives to net metering by legislatures and public utility commissions (PUCs), with some related deliberations underway or recently concluded in at least 48 states and the District of Columbia. These actions sometimes arise from preexisting legislative or regulatory requirements that trigger reviews when the total installed NEM system capacity or energy production, either for individual utilities or statewide, reaches a predetermined threshold. In other cases, regulatory reviews have been requested by utility companies through proposals to replace net-metering with other alternatives. Alternative proposals to supplant net metering include rate designs with various combinations of: (a) compensating for energy delivered to the grid at a price other than the retail service rate; (b) increasing fixed charges and sometimes also minimum bills; (c) time-varying rates; and (d) adding demand-charges to bills for customers who did not previously have them. Several states have considered creating a separate rate class for customers with distributed generation (DG), whereas others have made provisions for utility ownership of DG under specific circumstances. Another important factor included in this review is the treatment of customers who entered into NEM arrangements under previous rate designs. There is often some provision for grandfathering, allowing customers to continue operating under a previous rate design for some period after the new rate becomes effective. In some jurisdictions, the proposed or adopted changes affect all residential and small commercial customers, whereas in others the changes apply only to NEM customers. In some jurisdictions, NEM or successor rate designs also apply to customers participating in variations of aggregated, neighborhood, or virtual net metering, which often also includes participants in community-solar projects. The rates for community solar participants are often somewhat different from customers with on-site DG, but they are sometimes considered part of the same overall tariff. This NRRI briefing paper includes reviews of changes to NEM or DG program rate designs. The changes resulted from either new legislation that directs state commissions to make changes, or changes that state public utility regulatory commission have already adopted, or both. The review encompasses legislative changes that have occurred since 2014 and regulatory changes that took effect by mid-2018 or earlier. It draws from and expands upon information provided in the North Carolina Clean Energy Technology Center’s 50 States of Solar series; particularly, the 4th Quarter Report and Annual Summary for 2017 (2018a) and Q1 and Q2 2018 Update Reports (2018b and 2018c).

Key Takeaways
  • Many utilities and some other interested parties subsequently described NEM as a program that was inherently causing cross-subsidies to be paid by non-participating customers to participating customers.
  • NEM programs, originally intended to support nascent markets for marginally cost-effective solar PV, have served their purpose and the time has come to replace them with cost-based or value-based tariffs.
  • Exports from NEM customers are a service that the customer provides to the utility system, and the regulatory treatment should appropriately compensate NEM customers for the services they are producing and delivering
  • Including subsidy for distributed solar in DG cost calculation is a complex question, which cannot be answered without detailed analysis, utility by utility
  • Solar market moved from Uneconomic, to Pre-economic and is now competitive to grid electricity
  • There are already roughly two dozen completed studies in over one dozen states (RMI 2013; Taylor, McLaren et al. 2015) to determine whether VOS should be based on the value of solar, cost of solar, or a mix of the two. Interestingly, there is little consistency in the findings from those studies to date.
  • The studies have not all included the same list of potential benefits or costs, nor have they all used the same measurement methods. Thus, the resulting values range widely, from as little as 4¢/kWh to as much as 30¢/kWh, with a mean value of 16¢/kWh (RMI 2013).
  • At present, there is no “one size fits all” system for completing these studies: fundamental differences of opinions remain among different interested parties about both the identification of benefit and cost categories to be included, and the appropriate methods and time horizons to use for estimating what those benefits and costs might be.
  • There is a recognition that distributed resources are generally more valuable than bulk power in the wholesale market, due mainly to cost savings because of:
  1. Reduced transmission and distribution system losses
  2. Estimated value for environmental benefits
  • On the other hand, several studies have also concluded that distributed resources are less valuable than the full retail rate
  • VOS prices do not apply to all type of customers
  • The state of Georgia identified nine distributed generation cost components providing a net benefit, six components providing a cost, and two components providing either a cost or a benefit.
  • A 2014 Mississippi VOS study concluded that VOS was positive under all but one of the scenarios and sensitivities studied.
  • Remaining question: Are studies of VOS, VDER, and utility costs of service measuring the right benefits and costs? Are they measuring all of them? And are the measuring methods valid and reliable?

The 50 States of Solar: 2019 Policy Review Q4 2019 Quarterly Report[edit | edit source]

  • Citation

Proudlove, Autumn, Brian Lips, and David Sarkisian. “The 50 States of Solar: 2019 Policy Review Q4 2019 Quarterly Report.” NC CLEAN ENERGY TECHNOLOGY CENTER, January 2020.

  • Key Takeaways:
Topics of interest to us in the report
  • Significant changes to state or utility net metering laws and rules, including program caps, system size limits, meter aggregation rules, and compensation rates for net excess generation
  • Legislative or regulatory-led efforts to study the value of solar, net metering, or distributed solar generation policy, e.g., through a regulatory docket or a cost-benefit analysis
Increasing Solar market in the US as for end of 2019
Policy changes in discussion in most US States
In 2019, state and utility solar policies were undergoing review in nearly every state in the country, with 46 states and DC considering changes in 2019
Changes need to be done to fairly compensate new participant to the interconnected electricity grid web
States are conducting Extensive Value of Solar Studies to Inform Net Metering Successors
Table 2 in the report describes DG Compensation and Credit Rate Structures
DISTRIBUTED SOLAR VALUATION STUDIES REVIEW
  • In 2019, 22 states plus DC were in the process of examining some element of the value of distributed generation.
  • A study quantifying the value of distributed solar was completed in Mississippi.
  • New DG valuation studies were launched in Connecticut and South Carolina, while utilities in Minnesota and Oregon filed updated value of solar calculations
Value Of solar study components
  • Integration Cost
  • Administrative Cost
  • Avoided Energy
  • Avoided Generation Capacity
  • Avoided Transmission
  • Avoided Distribution
  • System/Line Losses
  • Ancillary Services
  • Risk/Price Hedging
  • Market Price Suppression
  • Environmental Benefits
Table 5 gives another list of component included in the valuation of solar in 3 US states

The Value of Solar Writ Large: A Modest Proposal for Applying ‘Value of Solar’ Analysis and Principles to the Entire Electricity Market[edit | edit source]

The Value of Solar Writ Large: A Modest Proposal for Applying ‘Value of Solar’ Analysis and Principles to the Entire Electricity Market

  • Citation

Brown, Ashley C. “The Value of Solar Writ Large: A Modest Proposal for Applying ‘Value of Solar’ Analysis and Principles to the Entire Electricity Market.” The Electricity Journal 29, no. 9 (November 2016): 27–30. https://doi.org/10.1016/j.tej.2016.10.009.

  • Abstract

The essay sets out what electric markets might look like if the pricing proposed in value of solar studies were adopted for every resource.

  • Key Takeaways
Criteria include in calculation of VOS
  • Grid management benefits (e.g. dispatch, congestion, line losses, and ancillary services); :*Grid capacity benefits :*Generation benefits (including generating capacity)
  • Carbon and other environmental benefits
  • Jobs benefits
  • Fuel and price hedge benefits
This paper argues that other sources of energy have the same benefits

The Reliability of Distributed Solar in Critical Peak Demand: A Capital Value Assessment[edit | edit source]

The Reliability of Distributed Solar in Critical Peak Demand: A Capital Value Assessment

  • Citation

Burke, Kerry B. “The Reliability of Distributed Solar in Critical Peak Demand: A Capital Value Assessment.” Renewable Energy 68 (August 2014): 103–10. https://doi.org/10.1016/j.renene.2014.01.042.

  • Abstract

Generation is most valuable when demand is highest. As electricity can’t yet be cheaply stored, generation and transmission infrastructure must be built to meet the highest expected demand, plus a margin of error.Reliably producing power at times of critical demand not only offsets the need to use expensive liquid fuels such as diesel or condensate, but also removes the need to build backup power stations and transmission infrastructure that would only be used for a small fraction of the year. Under the most extreme demand conditions, solar has reduced the peak demand seen by retailers and wholesale energy markets. This study compares the capital cost of critical peak availability from gas turbines to the capital cost of critical peak availability from distributed solar in the Australian National Electricity Market (NEM). When compared on this basis, 10e22% of the cost of installing the solar system can be attributed to the capital value of critical peak generation. Northwest and west facing PV is worth a further 3e6% of system installation costs when compared to generally north facing PV. Finally, southern states, with longer summer days and more sun-shine in the afternoon are found to benefit more from peak supply of solar PV

  • Key Takeaways
This paper aims to assess the value of distributed solar PV’s availability in times of critical peak demand, rather than calculating an average value of energy.
Importance of having reliable data
Power output as a percentage of rated capacity calculated for every half hour over the last two summers
Cost evaluation of solar consideration
  • Gas turbine nameplate construction cost
  • Temperature effects of generation: temperature lower efficiency of gas turbine in summer
  • Losses: Transport and distribution
  • Effective peak capacity costs
This study makes no attempt to calculate the avoided costs of delayed transmission and distribution infrastructure upgrades.Such a calculation is not possible without substation level load data from distribution companies.
This study makes no attempt to calculate the value of energy produced by distributed solar PV. The value of critical peak capacity is additional to the value of energy produced as calculated by regulatory bodies.

Distributed Energy Resources and Benefits to the Environment[edit | edit source]

Distributed Energy Resources and Benefits to the Environment

  • Citation

Akorede, Mudathir Funsho, Hashim Hizam, and Edris Pouresmaeil. “Distributed Energy Resources and Benefits to the Environment.” Renewable and Sustainable Energy Reviews 14, no. 2 (February 1, 2010): 724–34. https://doi.org/10.1016/j.rser.2009.10.025.

  • Abstract

The recently released report of the International Energy Outlook (IEO2009) projects an increase of 44% in the world energy demand from 2006 to 2030, and 77% rise in the net electricity generation worldwide in the same period. However, threatening in the said report is that 80% of the total generation in 2030 would be produced from fossil fuels. This global dependence on fossil fuels is dangerous to our environment in terms of their emissions unless specific policies and measures are put in place. Nevertheless, recent research reveals that a reduction in the emissions of these gases is possible with widespread adoption of distributed generation (DG) technologies that feed on renewable energy sources, in the generation of electric power. This paper gives a detailed overview of distributed energy resources technologies, and also discusses the devastating impacts of the conventional power plants feeding on fossil fuels to our environment. The study finally justifies how DG technologies could substantially reduce greenhouse gas emissions when fully adopted; hence, reducing the public concerns over human health risks caused by the conventional method of electricity generation.

  • Key Takeaways:
It is generally anticipated that traditional fossil fuels would be phased out over time by renewable energy sources. The reason is majorly due to the global concerns over the amount of GHGs emitted to the atmosphere when these fuels are burnt for one purpose or another.
Recent studies have revealed that wide-spread adoption of distributed generation (DG) technologies in power systems can play a key role in creating a clean, reliable energy with substantial environmental and other benefits
Environmental advantages of Distributed Generation
  • Promotion of higher efficiency
  • Reduction in greenhouse gas emissions due to power generation
  • Minimizes damage to health
  • Space saving advantage
Finding another energy sources such as distributed generation that feed on renewable energy sources would not only help meet the growing energy demand but also preserve our environment from the devastating effects of GHGs caused by the traditional method

The Climate and Air-Quality Benefits of Wind and Solar Power in the United States[edit | edit source]

The Climate and Air-Quality Benefits of Wind and Solar Power in the United States

  • Citation

Millstein, Dev, Ryan Wiser, Mark Bolinger, and Galen Barbose. “The Climate and Air-Quality Benefits of Wind and Solar Power in the United States.” Nature Energy 2, no. 9 (September 2017): 17134. https://doi.org/10.1038/nenergy.2017.134.

  • Abstract

Wind and solar energy reduce combustion-based electricity generation and provide air quality and greenhouse gas emission benefits. These benefits vary dramatically by region and over time. From 2007 –2015, solar and wind power deployment increased rapidly while regulatory changes and fossil fuel price changes led to steep cuts in overall power-sector emissions.Here we evaluate how wind and solar climate and air quality benefits evolved during this time period. We find cumulative wind and solar air quality benefits of 29.7 –112.8 billion US 2015$ mostly from 3,000 –12,700 avoided premature mortalities, and cumulative climate benefits of5.3 –106.8billion US 2015$. The ranges span results across a suite of air quality and health impact models and social cost of carbon estimates. We find that binding cap-and-trade pollutant markets may have reduced these cumulative benefits by up to 16%. In 2015, based on central estimates, combined marginal benefits equal 7.3¢/kWh (wind) and 4.0 ¢/kWh (solar).

  • Key Takeaways:
Air Emission Impact
AVERT
Valuation of Air Quality Benefits
EASIUR, EPA RIA, and COBRA
Valuation of GHG Emission Reductions
Literature

The environmental and public health benefits of achieving high penetrations of solar energy in the United States[edit | edit source]

The environmental and public health benefits of achieving high penetrations of solar energy in the United States

  • Citation

Wiser, Ryan, Dev Millstein, Trieu Mai, Jordan Macknick, Alberta Carpenter, Stuart Cohen, Wesley Cole, Bethany Frew, and Garvin Heath. “The Environmental and Public Health Benefits of Achieving High Penetrations of Solar Energy in the United States.” Energy 113 (October 15, 2016): 472–86. https://doi.org/10.1016/j.energy.2016.07.068.

  • Abstract

We estimate the environmental and public health benefits that may be realized if solar energy cost reductions continue until solar power is competitive across the U.S. without subsidies. Specifically, we model, from 2015 to 2050, solar power–induced reductions to greenhouse gas (GHG) emissions, air pollutant emissions, and water usage. To find the incremental benefits of new solar deployment, we compare the difference between two scenarios, one where solar costs have fallen such that solar supplies 14% of the nation's electricity by 2030 and 27% by 2050, and a baseline scenario in which no solar is added after 2014. We monetize benefits, where credible methods exist to do so. We find that under these scenarios, solar power reduces GHG and air pollutants by ∼10%, from 2015 to 2050, providing a discounted present value of $56–$789 billion (central value of ∼$250 billion, equivalent to ∼2 ¢/kWh-solar) in climate benefits and $77–$298 billion (central value of $167 billion, or ∼1.4 ¢/kWh-solar) in air quality and public health benefits. The ranges reflect uncertainty within the literature about the marginal impact of emissions of GHG and air pollutants. Solar power is also found to reduce water withdrawals and consumption by 4% and 9%, respectively, including in many drought-prone states.

  • Key Takeaways:
GHG emissions valuation
Social Cost of Carbon (SCC)
SO2,NOx and primary PM2.5 emissions valuation - Peer reviewed methods
  • Air Pollution Emission Experiments and Policy analysis model (AP2,formerly APEEP; described in Muller et al.[69])
  • EPA's marginal benefit methodology developed for the CPP[31,33]
  • Water usage valuation: not evaluated in this study

Air quality and health co-benefits of China's national emission trading system[edit | edit source]

Air quality and health co-benefits of China's national emission trading system

  • Citation

Chang, Shiyan, Xi Yang, Haotian Zheng, Shuxiao Wang, and Xiliang Zhang. “Air Quality and Health Co-Benefits of China’s National Emission Trading System.” Applied Energy 261 (March 1, 2020): 114226. https://doi.org/10.1016/j.apenergy.2019.114226.

  • Abstract

Quantification of the air quality and health co-benefits of climate policies can provide explicit near-term localized assessment of the benefits of efforts to mitigate climate change. In the study, the air quality and PM2.5 associated health co-benefits of China's national Emission Trading System to achieve the Nationally Determined Contribution is analyzed. The interdisciplinary integrated assessment model framework, named the Regional Emissions Air quality Climate Health Model, is applied. The results showed that substantial air quality improvement and health benefit will be achieved under the national Emission Trading System. But the cost and benefits varies according to the CO2 emission cap set. To peak CO2 emissions by 2025 will bring about more obvious improvement in air quality (ranging from 3% to 12% PM2.5 concentration reduction at provincial level compared with that to peak CO2 emission by 2030), more morbidities avoided from acute exposure and more mortalities avoided from acute exposure and chronic exposure. While the net health benefit to achieve peaking by 2025 is US$ 100 billion less than that to achieve peaking by 2030 due to greater GDP loss in 2030. The net benefit is subjected to the valuation of the health benefits. If a higher Value of a Statistical Life, US$ 1.92 million, is chosen, the net benefits to achieve peak CO2 emissions by 2025 can be equal to that to achieve peak CO2 emissions by 2030.

  • Key Takeaways:
  • Analysis of CO2, PM2.5 and health effects

Potential air quality benefits from increased solar photovoltaic electricity generation in the Eastern United States[edit | edit source]

Potential air quality benefits from increased solar photovoltaic electricity generation in the Eastern United States

  • Citation

Abel, David, Tracey Holloway, Monica Harkey, Arber Rrushaj, Greg Brinkman, Phillip Duran, Mark Janssen, and Paul Denholm. “Potential Air Quality Benefits from Increased Solar Photovoltaic Electricity Generation in the Eastern United States.” Atmospheric Environment 175 (February 1, 2018): 65–74. https://doi.org/10.1016/j.atmosenv.2017.11.049.

  • Abstract

We evaluate how fine particulate matter (PM2.5) and precursor emissions could be reduced if 17% of electricity generation was replaced with solar photovoltaics (PV) in the Eastern United States. Electricity generation is simulated using Grid View, then used to scale electricity-sector emissions of sulfur dioxide (SO2) and nitrogen oxides (NOX) from an existing gridded inventory of air emissions. This approach offers a novel method to leverage advanced electricity simulations with state-of-the-art emissions inventories, without necessitating recalculation of emissions for each facility. The baseline and perturbed emissions are input to the Community Multiscale Air Quality Model (CMAQ version 4.7.1) for a full accounting of time- and space-varying air quality changes associated with the 17% PV scenario. These results offer a high-value opportunity to evaluate the reduced-form Avoided Emissions and generation Tool (AVERT), while using AVERT to test the sensitivity of results to changing base-years and levels of solar integration. We find that average NOX and SO2 emissions across the region decrease 20% and 15%, respectively. PM2.5 concentrations decreased on average 4.7% across the Eastern U.S., with nitrate (NO3−) PM2.5 decreasing 3.7% and sulfate (SO42−) PM2.5 decreasing 9.1%. In the five largest cities in the region, we find that the most polluted days show the most significant PM2.5 decrease under the 17% PV generation scenario, and that the greatest benefits are accrued to cities in or near the Ohio River Valley. We find summer health benefits from reduced PM2.5 exposure estimated as 1424 avoided premature deaths (95% Confidence Interval (CI): 284 deaths, 2 732 deaths) or a health savings of $13.1 billion (95% CI: $0.6 billion, $43.9 billion) These results highlight the potential for renewable energy as a tool for air quality managers to support current and future health-based air quality regulations.

  • Key Takeaways:
Solar PV environmental impact Analysis methods presented
Element analyzed
  • Generation
  • Emissions
  • Air quality
  • Health impacts
  • Sensitivity testing

Measuring Renewable Energy Externalities: Evidence from Subjective Well-Being Data[edit | edit source]

Measuring Renewable Energy Externalities: Evidence from Subjective Well-Being Data

  • Citation

Möllendorff, Charlotte von, and Heinz Welsch. “Measuring Renewable Energy Externalities: Evidence from Subjective Well-Being Data.” Land Economics 93, no. 1 (February 1, 2017): 109–26. https://doi.org/10.3368/le.93.1.109.

  • Abstract

Electricity from renewable sources avoids disadvantages of conventional power generation but often meets with local resistance. We use 324,763 observations on the subjective well-being of46,678 individuals in Germany, 1994–2012, for identifying and valuing the local externalities from solar,wind, and biomass plants in respondents’ postcode district and adjacent postcode districts. We find significant wellbeing externalities of all three technologies that differ with regard to their temporal and spatial characteristics. The monetary equivalent of 1MW capacity expansion of wind power and biomass installations is estimated to be 0.35% and 1.25% of monthly per capita income, respectively.(JEL D62,Q42)

  • Key Takeaways:
Welsch and Biermann(2014) found in a multi-country study that a higher share of solar and wind power in a country’s national electricity mix is associated with greater subjective well-being of its citizens.
Renewables sometimes, meet with local resistance because of social and community acceptance
This paper studies RE externalities from the point of view of local subjective well-being
The paper found out that renewable power plants generate statistically and economically significant local externalities whose effects differ across the technologies considered, both qualitatively and quantitatively.
The study used nationwide representative data
Limitations
No differentiation between rooftop solar and free-stand solar
The monetary estimation of externalities depends on location (local income level)
There should be a trade-off between the externalities of RE and fossil sources

Analyzing the Costs and Benefits of Distributed Solar Generation in Virginia[edit | edit source]

Analyzing the Costs and Benefits of Distributed Solar Generation in Virginia

  • Citation

Pitt, Damian, and Gilbert Michaud. “Analyzing the Costs and Benefits of Distributed Solar Generation in Virginia,” n.d., 70.

  • Abstract

Distributed solar energy has recently become the subject of heated policy debate in Virginia and many other states. Proponents note that it provides a variety of environmental, public health, and economic development benefits for society. They also argue that it can help electric utilities save money on conventional generation fuels, avoid new generation capacity investments, and reduce the strain on existing transmission and distribution infrastructure. However,many electric utilities, including those in Virginia, argue that distributed solar energy creates costs for utilities that will then be passed on to ratepayers. For example, a dramatic increase in distributed solar energy could theoretically reduce utilities’ revenue to the point that they cannot pay off existing investments in generation infrastructure, creating “stranded asset” costs. The utilities also contend that expanded solar deployment may not reduce the need for additional conventional generation capacity, and that it could cause technical problems for the transmission and distribution grids. This report seeks to provide a better understanding of the costs and benefits of solar energy in Virginia, including its impacts to utilities, ratepayers, and society at large. It does not produce a single figure for the net value of distributed solar generation (DSG). Instead, it discusses the variables that should be included when evaluating the costs and benefits of DSG, and recommends three alternative methods by which subsequent studies could calculate those costs and benefits. It also discusses how the costs and benefits of DSG could be influenced by future market, technology, or policy changes, but it does not offer any policy recommendations. Rather, its purpose is to provide an impartial analysis of the value of solar in order to better inform the policy debate around solar energy issues.

  • Key Takeaways:
Component of VOS in the case of Virginia
  • Avoided energy
  • Generation capacity
  • Transmission Energy
  • Distribution Energy
  • Carbon emissions
  • Other air pollutants
  • Water impacts
  • Economic development
  • Fuel price volatility
  • Reliability risk
  • Market price response
  • Land impacts
  • Ancillary services

Assessing the Value of Distributed Solar Energy Generation[edit | edit source]

Assessing the Value of Distributed Solar Energy Generation

  • Citation

Pitt, Damian, and Gilbert Michaud. “Assessing the Value of Distributed Solar Energy Generation.” Current Sustainable/Renewable Energy Reports 2, no. 3 (2015): 105–113. https://doi.org/10.1007/s40518-015-0030-0.

  • Abstract

Solar energy has recently become the subject of heated policy debate across the United States, particularly at the state level. Proponents note that it provides a variety of environmental, public health, and economic development benefits for society and argue that it can help support electric grid operations. Many electric utilities, however, contend that the growth of customer-owned, distributed solar energy systems will create costs that the utilities must pass on to ratepayers. This debate has led to a wide range of technical reports seeking to quantify the costs and benefits of solar energy to electric utilities, ratepayers, and society at large. We review these studies, discuss the different perspectives that they represent, and identify the key variables that have shaped this value-of-solar debate. We conclude by discussing future research opportunities that could help to maximize the benefits of solar energy use while minimizing its potential negative impacts.

  • Key Takeaways:
The paper states the reasons why solar valuation opponents are against the principle
The paper reviews the current policy debate on distributed solar energy and the ongoing research efforts to identify the true value of solar(VOS) for electric utilities, their customers, and society at large
Features involved in VOS calculation
  • Avoided Energy Costs
  • Generation Capacity
  • Transmission and Distribution Grid Impacts
  • Natural Gas Market Impacts
  • Environmental Benefits
  • Economic Development
VOS debate is largely a matter of perspective, as the costs and benefits vary widely based
  • the time frame considered
  • assumed market penetration
  • values incorporated
The negative environmental impacts of conventional electricity generation are generally not captured by existing regulatory and market structures, and as such, they are often not addressed in official studies for electric utilities and public utility commissions

Can Distributed Generation Offer Substantial Benefits in a Northeastern American Context? A Case Study of Small-Scale Renewable Technologies Using a Life Cycle Methodology[edit | edit source]

Can Distributed Generation Offer Substantial Benefits in a Northeastern American Context? A Case Study of Small-Scale Renewable Technologies Using a Life Cycle Methodology

  • Citation

Amor, Mourad Ben, Pascal Lesage, Pierre-Olivier Pineau, and Réjean Samson. “Can Distributed Generation Offer Substantial Benefits in a Northeastern American Context? A Case Study of Small-Scale Renewable Technologies Using a Life Cycle Methodology.” Renewable and Sustainable Energy Reviews 14, no. 9 (2010): 2885–2895. https://doi.org/10.1016/j.rser.2010.08.001.

  • Abstract

Renewable distributed electricity generation can play a significant role in meeting today's energy policy goals, such as reducing greenhouse gas emissions, improving energy security, while adding supply to meet increasing energy demand. However, the exact potential benefits are still a matter of debate. The objective of this study is to evaluate the life cycle implications (environmental, economic and energy) of distributed generation (DG) technologies. A complementary objective is to compare the life cycle implications of DG technologies with the centralized electricity production representing the Northeastern American context. Environmental and energy implications are modeled according to the recommendations in the ISO 14040 standard and this, using different indicators: Human Health; Ecosystem Quality; Climate Change; Resources and Non-Renewable Energy Payback Ratio. Distinctly, economic implications are modeled using conventional life cycle costing. DG technologies include two types of grid-connected photovoltaic panels (3 kWp mono-crystalline and poly-crystalline) and three types of micro-wind turbines (1, 10 and 30 kW) modeled for average, below average and above average climatic conditions in the province of Quebec (Canada). A sensitivity analysis was also performed using different scenarios of centralized energy systems based on average and marginal (short- and long-term) technology approaches. Results show the following. First, climatic conditions (i.e., geographic location) have a significant effect on the results for the environmental, economic and energy indicators. More specifically, it was shown that the 30 kW micro-wind turbine is the best technology for above average conditions, while 3 kWp poly-crystalline photovoltaic panels are preferable for below average conditions. Second, the assessed DG technologies do not show benefits in comparison to the centralized Quebec grid mix (average technology approach). On the other hand, the 30 kW micro-wind turbine shows a potential benefit as long as the Northeastern American electricity market is considered (i.e., oil and coal centralized technologies are affected for the short- and long-term marginal scenarios, respectively). Photovoltaic panels could also become more competitive if the acquisition cost decreased. In conclusion, DG utilization will represent an improvement over centralized electricity production in a Northeastern American context, with respect to the environmental, energy and economic indicators assessed, and under the appropriate conditions discussed (i.e., geographical locations and affected centralized electricity production scenarios).

  • Key Takeaways:
Comparison of life cycle impact of renewables to fossils
Studies included geographical dependencies
The externalities value in VOS depends on geographical location

Climate, Air Quality and Human Health Benefits of Various Solar Photovoltaic Deployment Scenarios in China in 2030[edit | edit source]

Climate, Air Quality and Human Health Benefits of Various Solar Photovoltaic Deployment Scenarios in China in 2030

  • Citation

Yang, Junnan, Xiaoyuan Li, Wei Peng, Fabian Wagner, and Denise L. Mauzerall. “Climate, Air Quality and Human Health Benefits of Various Solar Photovoltaic Deployment Scenarios in China in 2030.” Environmental Research Letters 13, no. 6 (2018): 10. https://doi.org/10.1088/1748-9326/aabe99.

  • Abstract

Solar photovoltaic (PV) electricity generation can greatly reduce both air pollutant and greenhouse gas emissions compared to fossil fuel electricity generation. The Chinese government plans to greatly scale up solar PV installation between now and 2030. However, different PV development pathways will influence the range of air quality and climate benefits. Benefits depend on how much electricity generated from PV is integrated into power grids and the type of power plant displaced. Using a coal-intensive power sector projection as the base case, we estimate the climate, air quality, and related human health benefits of various 2030 PV deployment scenarios. We use the 2030 government goal of 400 GW installed capacity but vary the location of PV installation and the extent of inter-provincial PV electricity transmission. We find that deploying distributed PV in the east with inter-provincial transmission maximizes potential CO2 reductions and air quality-related health benefits (4.2% and 1.2% decrease in national total CO2 emissions and air pollution-related premature deaths compared to the base case, respectively). Deployment in the east with inter-provincial transmission results in the largest benefits because it maximizes displacement of the dirtiest coal-fired power plants and minimizes PV curtailment, which is more likely to occur without inter-provincial transmission. We further find that the maximum co-benefits achieved with deploying PV in the east and enabling inter-provincial transmission are robust under various maximum PV penetration levels in both provincial and regional grids. We find large potential benefits of policies that encourage distributed PV deployment and facilitate inter-provincial PV electricity transmission in China.

  • Key Takeaways:
This paper conducts an integrated assessment that quantifies and compares the climate, air quality, and related human health benefits of various solar PV deployment and utilization scenarios for 2030 China
The study demonstrates not only the increased air quality and climate co-benefits of installing distributed PV in the east, but also the fact that the air quality and climate co-benefits would likely be reduced due to PV curtailment in the northwest
Environmental benefits of solar PV depends on the location

Solar Regime and LVOE of PV Embedded Generation Systems in Nigeria[edit | edit source]

Solar Regime and LVOE of PV Embedded Generation Systems in Nigeria

  • Citation

Ohijeagbon, O. D., and Oluseyi O. Ajayi. “Solar Regime and LVOE of PV Embedded Generation Systems in Nigeria.” Renewable Energy 78 (2015): 226–235. https://doi.org/10.1016/j.renene.2015.01.014.

  • Abstract

The study assessed the potential and economic viability of solar PV standalone systems for embedded generation, taking into account its benefits to small off-grid rural communities in forty meteorological sites in Nigeria. A specific electric load profile was developed to suite the communities consisting 200 homes, a school and community health centre. Data (daily mean relative humidity, maximum and minimum temperatures, and daily global solar radiation for 24 years spanning 1987-2010) obtained from the Nigeria Meteorological Agency were used. It focused on the assessment of design that will optimally meet daily load demand for the rural communities with an LOLP of 0.01. The HOMER® software optimizing tool was engaged for the feasibility study and design. A 15 MW PV distributed generation system was utilized to economically compare the different sites in terms of life cycle cost as well as levelised cost of producing energy. A profit for potential investors in the range of $ 0.01/kWh to $ 0.17/kWh was discovered for 29 of the 40 available meteorological sites, while the remaining sites were not profitable with the present tariff regime in Nigeria.

  • Key Takeaways:
Calculation of LCOE for Solar in Nigeria

Regional Variations in the Health, Environmental, and Climate Benefits of Wind and Solar Generation[edit | edit source]

Regional Variations in the Health, Environmental, and Climate Benefits of Wind and Solar Generation

  • Citation

Siler-Evans, Kyle, Inês Lima Azevedo, M. Granger Morgan, and Jay Apt. “Regional Variations in the Health, Environmental, and Climate Benefits of Wind and Solar Generation.” Proceedings of the National Academy of Sciences of the United States of America 110, no. 29 (2013): 11768–11773. https://doi.org/10.1073/pnas.1221978110.

  • Abstract

When wind or solar energy displace conventional generation, the reduction in emissions varies dramatically across the United States. Although the Southwest has the greatest solar resource, a solar panel in New Jersey displaces significantly more sulfur dioxide, nitrogen oxides, and particulate matter than a panel in Arizona, resulting in 15 times more health and environmental benefits. A wind turbine in West Virginia displaces twice as much carbon dioxide as the same turbine in California. Depending on location, we estimate that the combined health, environmental, and climate benefits from wind or solar range from $10/MWh to $100/MWh, and the sites with the highest energy output do not yield the greatest social benefits in many cases. We estimate that the social benefits from existing wind farms are roughly 60% higher than the cost of the Production Tax Credit, an important federal subsidy for wind energy. However, that same investment could achieve greater health, environmental, and climate benefits if it were differentiated by region.

  • Key Takeaways:
The paper estimates the monetized social benefits resulting from emissions reductions, and we explicitly consider differences in energy production, climate benefits from displaced CO2emissions, and health and environmental benefits from displaced SO2, NOx, and PM2.5
Damages from CO2 emissions are monetized using a social cost of $20 per ton of CO2.
Location-specific damages from SO2, NOx, and PM2.5 emissions are adopted from the Air Pollution Emission Experiments and Policy(APEEP) analysis model, which values mortality from air pollution at $6 million per life lost (often termed the value of a statistical life)

Designing Compensation for Distributed Solar Generation:Is Net Metering Ever Optimal[edit | edit source]

Designing Compensation for Distributed Solar Generation:Is Net Metering Ever Optimal

  • Citation

Brown, David P., and David E. M. Sappington. “Designing Compensation for Distributed Solar Generation:Is Net Metering Ever Optimal?” The Energy Journal 38, no. 3 (July 1, 2017). https://doi.org/10.5547/01956574.38.3.dbro.

  • Abstract

Electricity customers who install solar panels often are paid the prevailing retail price for the electricity they generate. We demonstrate that this rate of compensation typically is not optimal. A payment for distributed generation (w) that is below the retail price of electricity (r) often will induce the welfare-maximizing level of distributed generation (DG) when the fixed costs of centralized electricity production and the network management costs of accommodating intermittent solar DG are large, and when centralized generation and DG produce similar(pollution) externalities. w can optimally exceed r under alternative conditions.The optimal DG compensation policy varies considerably as industry conditions change. Furthermore, a requirement to equate w and r can reduce aggregate welfare substantially and can generate pronounced distributional effects.

  • Key Takeaways:
Proposed Equation for VOS components calculation
externalities

Distributed Generation Valuation and Compensation[edit | edit source]

Distributed Generation Valuation and Compensation

  • Citation

Orrell, Alice C., Juliet S. Homer, and Yingying Tang. “Distributed Generation Valuation and Compensation,” February 14, 2018. https://doi.org/10.2172/1561273.

  • Abstract

This white paper can help guide a state as it considers issues associated with distributed generation valuation and compensation. States may address a common set of questions and issues in the valuation process, but differences in market expectations, policy priorities, and regulations result in different responses. Key issues include the following:

  • Context is important. Valuations and compensation strategies will vary based on goals and objectives they are being designed to achieve. Goals and objectives should be made clear up front and will drive the perspective used in performing valuations and how outcomes are applied.
  • An important early step in performing valuations is to survey the different value components and their associated costs and benefits that could be used as the valuation building blocks. Examples of valuation building blocks include avoided costs associated with fuel, generation capacity, transmission capacity, reserve capacity, distribution capacity, fixed and variable operations, and maintenance and environmental compliance and/or impacts.
  • Utilities and stakeholders can have different interpretations of how value elements should be calculated. In some states, the objective of standardized calculators and methods is to reduce ambiguity and inconsistencies in how valuations are performed.
  • Certain value elements are difficult or impossible to quantify and most efforts to establish workable value of solar or value of distributed energy resource tariffs are emerging and nascent. Assessing locational and temporal value of distributed generation and applying that in compensation schemes is a new and emerging field of study being explored by a handful of research organizations and advanced states and utilities.
  • The most advanced states, such as California, are using demonstration projects to test valuation and compensation methodologies or are applying valuation and compensation strategies to a subset of customer projects, such as for community solar projects (e.g., Oregon and New York), before rolling out programs to the full customer base.
  • A variety of states are moving away from full net metering, in many cases substituting avoided cost rates (sometimes with an adder) in lieu of full retail rate compensation, instead of pursuing valuation of distributed energy resource approaches. For example, in Indiana a 25% adder is applied to average wholesale electricity prices and in Mississippi a 2.5 cents/kWh adder is applied to avoided cost rates. These adders appear to have been established through policy directives rather than comprehensive cost of service valuations.
  • Key Takeaways:
In a value of distributed generation calculation, all values, both positive (i.e., benefits) and negative (i.e., costs), are considered to achieve a net value. This allows for a well-designed compensation mechanism to be achieved that mitigates negative effects, reinforces positive effects, and supports the full and fair value of distributed generation to all stakeholders (NREL 2017)
Different components of VOS from different states has been described.

Distributed Solar Photovoltaic Cost-Benefit Framework Study: Considerations and Resources for Oklahoma[edit | edit source]

Distributed Solar Photovoltaic Cost-Benefit Framework Study: Considerations and Resources for Oklahoma

  • Citation

Holm, Alison, Jeffrey J Cook, Alexandra Y Aznar, Jason W Coughlin, and Benjamin Mow. “Distributed Solar Photovoltaic Cost-Benefit Framework Study: Considerations and Resources for Oklahoma,” September 5, 2019. https://doi.org/10.2172/1561512.

  • Key Takeaways:
VOS Components mentioned in the report
  • Energy production
  • Generation capacity
  • Transmission & distribution capacity deferrals
  • Transmission & distribution line losses
  • Environmental costs and benefits
  • Natural gas (or other fuel) price hedge
  • Disaster recovery (also called security/resiliency)
  • Reactive power control
  • Voltage control
  • Solar integration costs
  • Credit for local manufacturing & assembly
  • Market price reduction
  • High-value location credit for PV system
  • Economic development value
Different components cited above are applied according to the state but the overarching points are
  • Energy
  • T&D loss savings
  • Generator capacity
  • T&D capacity
  • Environmental costs and benefits (e.g., emissions reductions)
  • Ancillary services
  • Other (e.g., fuel price hedging, market-price suppression).

Distributed Rate Design: A Review of Early Approaches and Practical Considerations for Value of Solar Tariffs[edit | edit source]

Distributed Rate Design: A Review of Early Approaches and Practical Considerations for Value of Solar Tariffs

  • Citation

O’Shaughnessy, Eric, and Kristen Ardani. “Distributed Rate Design: A Review of Early Approaches and Practical Considerations for Value of Solar Tariffs.” The Electricity Journal 33, no. 3 (April 2020): 106713. https://doi.org/10.1016/j.tej.2020.106713.

  • Abstract

Value of solar tariffs are an emerging rate design for grid-tied distributed solar. Value of solar rate design reflects tradeoffs between theoretical and practical considerations. We review two early U.S. value of solar tariff case studies to identify these key considerations. The cases illustrate how rate makers have designed practical rates that reasonably approximate the value of solar given context-specific objectives and constraints. We describe four practical considerations for future value of solar tariff design.

Assessing the Value of Distributed Solar[edit | edit source]

Assessing the Value of Distributed Solar

  • Citation

Harari, Sara, and Nate Kaufman. “Assessing the Value of Distributed Solar.” Yale Center for Business and the Environment, 2017, 21.

  • Key Takeaways:
Component included in Value of Solar with sources
  • Avoided Energy Costs
  • Avoided capital and capacity investment in generation infrastructure
  • Avoided capital and capacity investment in T&D infrastructure
  • Avoided O&M costs
  • Increased grid resiliency and reliability
  • Avoided losses and other locational benefits
  • Environmental benefits
  • Job creation

U.S. Climate Change Law: A Decade of Flux and an Uncertain Future[edit | edit source]

U.S. Climate Change Law: A Decade of Flux and an Uncertain Future

  • Citation

Carlarne, Cinnamon Piñon. “U.S. Climate Change Law: A Decade of Flux and an Uncertain Future.” SSRN Electronic Journal, 2019. https://doi.org/10.2139/ssrn.3493812.

  • Abstract

Climate change is a defining feature of contemporary existence. It also poses fundamental challenges to the rule of law. As the scale of the climate crises swells, so too do efforts to develop innovative strategies for addressing climate change at the local, state, and national levels. This innovation is driven by necessity and is fueled by creative and determined actors from across the public and private sectors. But the pace of legal innovation is uneven, and the consistency of political leadership is erratic. Nowhere is this more evident than at the federal level in the United States, where presidential politics vividly demonstrate the degree to which we still lack a collective national vision for how to respond to climate change.

In this Article, I argue that as important as presidential leadership is, lawmakers and scholars should not focus myopically on the vagaries of presidential climate politics and federal climate law. Between 2009 and2019, the United States elected the most climate-friendly president in U.S. history and then replaced him with the most climate-skeptical president in U.S. history. Within this dramatic decade, notwithstanding the fluxes and flows in legal development at the federal level, there has been a steady stream of legal innovation by subnational and non-state actors. The interactions between national, subnational, and non-state climate governance efforts are one of the most under-explored dimensions of domestic climate change law. This Article addresses this gap by examining key developments in U.S. climate change law and policy over the period 2009 to 2019, to reveal how subnational and non-state initiatives complement and constrain the development of national climate change law and policy over time.

  • Key Takeaways:
Removal of federal support to Climate Action Plan, Climate Action Plan Strategy to Reduce Methane Emissions. The order also directs immediate review of the CPP; disbands the Interagency Working Group on the Social Cost of Greenhouse Gases and withdraws its reports on the social cost of carbon declaring them “no longer representative of governmental policy
The EPA’s estimates suggest that increases in particulate matter and ozone pollution could lead to thousands of premature deaths and increases in pollution-related illness, as compared to the baseline under the CPP.

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