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.
Page data
Type Literature review
Authors Koami S. Hayibo, Abhishek Ravindran, Sreekanth Menon, Akram Faridi
Published 2022
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