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Community Solar Lit Review

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Please leave any comments on the Discussion page (see tab above) 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.

Back ground

Searches

  • Google for Community Solar
  • Google for shared solar
  • Google for solar gardens

Major Journals

  • Elsevier
  • IEEE

Community Solar

“community shared solar” is defined as a solar-electric system that provides power and/or financial benefit to multiple community members.

David Feldman, Anna M. Brockway, Elaine Ulrich, and Robert Margolis,"Shared Solar: Current Landscape, Market Potential, and the Impact of Federal Securities Regulation" NREL,April 2015.[1].

Restrictions on Community solar

  • Uncertainty about the applicability of Securities and Exchange Commission (SEC) requirements i.e when and how shared solar program is considered as "security".
  • subject to regulation State and local laws.
  • uncertain tax credit applicability such as 25D for residential purposes only upto 30% which restricts off site solar plant users. Section 48 for business have ventures have similar difficulties.

What is security?

A security is an investment instrument issued by a corporation, government, or other organization that offers evidence of debt or equity. Any transaction that involves an investment of money in an enterprise, with an expectation of profits to be earned through the efforts of someone other than the investor, is a transaction involving a security. Community shared solar organizers must be sure to comply with both state and federal securities regulations, and avoid inadvertently offering a security.

There is a need of no action letter from SEC for shared solar project

To pass as Federal security there is a Howey Test criteria:

  • An investment of money
  • In a common enterprise
  • Based solely on the efforts of a promoter or a third party
  • For which there is an expectation of profits

To pass as state security there is Risk capital test criteria:

  • Funds are being raised for a business venture or enterprise
  • The transaction is offered indiscriminately to the public at large
  • The investors are substantially powerless to affect the success of the enterprise
  • The investors’ money is substantially at risk because it is inadequately secured.

Even if a project is classified as security there are exemptions

States having shared solar policies

  • Group net metering or VNM: California, Connecticut, Massachusetts, Maine, New Hampshire, Vermont
  • Statewide shared energy program: California, Colorado, Delaware, District of Columbia, Massachusetts, Minnesota
  • Incentives: Washington

Potential of Shared solar

It is estimated that 49% of households and 48% of businesses cannot host a PV system of adequate size on their property or virtually net meter an entire system themselves. By opening the market to these customers, shared solar could represent 32%–49% of the distributed PV market in 2020, growing cumulative PV deployment in 2015–2020 by 5.5–11.0 GW and representing $8.2–$16.3 billion of cumulative investment.


Jason Coughlin, Jennifer Grove, et al., "Guide to community solar: Utility, private, and non-profit project development"U.S. Department of Energy, 2011.

  • Great Overview of community shared solar
  • Three different models – group members to be located within the same utility service territory, require solar array. Also talks about some main methods of implementation - Comparison between three main models (Utility,Special purpose entity & Non profit)
  • Includes Various state policies to support community shared solar

Billing methods – Group billing, virtual net metering and joint ownership 1.Group billing – master metering, net metering ((total from utility – PV generation)/total participants) based on agreement 2.Virtual net metering – Credits appear on each individual customer’s bill, Colorado best example, Few examples of California, Colorado, Massachusetts, Delaware’s community solar program 3.Joint ownership – joint ownership between customer/owner and utility, businesses etc, Example of Maine and Washington’ s program

  • Tax policy & incentives
  • Security compliance – security laws are intended to protect individuals who provide financial support for a project with an expectation to receive profits from the efforts of others or with the expectation to receive a valuable benefit when the investor does not have control over managerial decisions of the venture.
  • Basic step by step guidelines for community solar program


Baylin, F. et al. "Economic Analysis Of Community Solar Heating Systems That Use Annual Cycle Thermal Energy Storage". (1981): n. pag. Web. 19 Jan. 2017.

  • Dated
  • Very technical detail about how to store heat in underground tanks
  • Multiple geographic locations and community sizes looked at

Asmus, Peter. "Exploring New Models Of Solar Energy Development". The Electricity Journal 21.3 (2008): 61-70. Web. 19 Jan. 2017.

  • Brings up "community choice aggregation", California legislation.
  • Well defined community solar definition
  • Solar shares
  • List and overview of current (up until 2008) community solar projects

The following were found using the search term "Community solar pv" on google scholar

Ashok, S. "Optimised Model For Community-Based Hybrid Energy System". Renewable Energy 32.7 (2007): 1155-1164. Web. 18 Jan. 2017.

  • Community 'microgrid' idea for rural area, case study in India
  • Uses multiple generation sources; wind, hydro, solar, and tries to minimize cost of each
  • 'dated' -> optimization plan results in not choosing PV due to cost, although it was included originally.

Noll, Daniel, Colleen Dawes, and Varun Rai. "Community Organizations And Active Peer Effects In The Adoption Of Residential Solar PV". SSRN Electronic Journal 67 330-343. Web. 18 Jan. 2017.

  • Analyses of residential PV increase
  • Solar Community Organizations (SCOs)
  • Review of residential PV across U.S.

St. Denis, Genevieve and Paul Parker. "Community Energy Planning In Canada: The Role Of Renewable Energy". Renewable and Sustainable Energy Reviews 13.8 (2009): 2088-2095. Web. 19 Jan. 2017.

  • Large vs small communities and interest in renewable s
  • energy usage management
  • conservation and efficiency vs renewables

The following were found using the search term "Community solar projects" on google scholar

Walker, Gordon. "What Are The Barriers And Incentives For Community-Owned Means Of Energy Production And Use?". Energy Policy 36.12 (2008): 4401-4405. Web. 19 Jan. 2017.

  • cooperatives, community charities, etc -> diffenent community solar models
  • non-technical
  • high level overview

Huijben, J.C.C.M. and G.P.J. Verbong. "Breakthrough Without Subsidies? PV Business Model Experiments In The Netherlands". Energy Policy 56 (2013): 362-370. Web. 19 Jan. 2017.

  • micro generation deployment models, company control, plug and play, community microgrid
  • Main issues being legislation
  • Use of net metering

Palit, Debajit. "Solar Energy Programs For Rural Electrification: Experiences And Lessons From South Asia". Energy for Sustainable Development 17.3 (2013): 270-279. Web. 19 Jan. 2017.

  • Massive benefits to heavily populated rural areas
  • Some technical detail and policy
  • Recommendations

Seyfang, Gill, Jung Jin Park, and Adrian Smith. "A Thousand Flowers Blooming? An Examination Of Community Energy In The UK". Energy Policy 61 (2013): 977-989. Web. 19 Jan. 2017.

  • surveys among community energy groups in UK
  • development factors

Chaurey, A. and Kandpal, T.C., 2010. A techno-economic comparison of rural electrification based on solar home systems and PV microgrids. Energy policy, 38(6), pp.3118-3129. 22 Jan. 2017.

  • Off-grid PV power plants
  • Micro grids or mini grids distribution networks
  • Micro grid: more economic option for flat geographical terrains
  • Techno economic comparison of SHS and micro grids

Denis, G.S. and Parker, P., 2009. Community energy planning in Canada: The role of renewable energy. Renewable and Sustainable Energy Reviews, 13(8), pp.2088-2095. 23rd Jan 2017.

  • Renewable energy policy
  • Community energy plan
  • Community energy management
  • Energy conservation
  • Climate change policy

Shakouri, M., Lee, H.W. and Choi, K., 2015. PACPIM: new decision-support model of optimized portfolio analysis for community-based photovoltaic investment. Applied Energy, 156, pp.607-617. 23rd Jan 2017.

  • Solar energy
  • Community-based investments
  • Mean–Variance Portfolio theory
  • Decision-support model
  • Residential photovoltaic systems

Klein, S.J. and Coffey, S., 2016. Building a sustainable energy future, one community at a time. Renewable and Sustainable Energy Reviews, 60, pp.867-880. 24th Jan 2017

  • Community energy
  • Renewable energy
  • Sustainable energy
  • Grassroots innovation
  • Strategic niche management theory
  • Multi-level perspective

Funkhouser, E., Blackburn, G., Magee, C. and Rai, V., 2015. Business model innovations for deploying distributed generation: The emerging landscape of community solar in the US. Energy Research & Social Science, 10, pp.90-101. 24th Jan 2017

  • Community solar
  • Utility Business Model
  • Distributed generation
  • Net energy metering

ENERGY, N.C., 50States. 24th Jan 2017

  • US Distributed Solar Market
  • Net Metering Policy Changes
  • Community solar Policies
  • Proposed Charges on Residential Solar Customers
  • Third- party solar ownership
  • Utility-led Rooftop Solar Program Updates
  • Questions answered with this:

1. How are state regulatory bodies and legislatures and electric utilities addressing fast growing markets for distributed solar PV?

2. What changes to traditional rate design features and net metering policies are being proposed, approved, and implemented?

3. Where are distributed solar markets potentially affected by policy or regulatory decisions on community solar, third-party solar ownership, and utility-led residential rooftop solar programs?

  • Report include actions on:

1. Significant changes to state or utility net metering laws and rules, including aggregate caps, system size limits, aggregate net metering rules, and compensation rates for net excess generation.

2. Changes to statewide community solar laws and rules, and individual utility-sponsored community solar programs arising from statewide legislation.

3. 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.

4. Utility-initiated rate requests for charges applicable only to residential customers with solar PV or other types of distributed generation, such as added monthly fixed charges, demand charges, stand-by charges, or interconnection fees.

5. Utility-initiated rate requests that propose a 10% or larger increase in either fixed charges or minimum bills for all residential customers.

6. Changes to the legality of third-party solar ownership, including solar leasing and solar third-party solar PPAs, and proposed utility-led rooftop solar programs.

The growth in solar PV market is expected to continue, particularly due to the recent extension of the federal investment tax credit. The credit, which was previously set to expire for residential systems at the end of 2016, will be available at its current 30% level through 2019, then will step down over the next several years and expire at the end of 2021. The credit will remain at 10% permanently for commercial systems after 2021. GTM Research estimates that the extension of the federal investment tax credit will increase residential solar PV installations by 35% between 2016 and 2020 compared to a scenario without the extension.

TAX DETAILS[2]

  • The solar PV system is located at a residential location in the U.S.
  • You own the solar PV system (e.g., you purchased it with cash or through financing – but are not leasing it or in

an arrangement to purchase electricity generated by a system you do not own).

  • The solar PV system is new or being used for the first time. The ITC can only be claimed on the “original

installation” of the solar equipment.

  • It is not a necessity to be a homeowner to claim the tax credit. A tenant-stockholder at cooperative housing corporation and members of condominiums are still eligible for the tax credit if they contribute to the costs of an eligible solar PV system.
  • OFF-SITE COMMUNITY SOLAR PROGRAM: There is an example for this. "For example, one arrangement is the creation of a “Special Purpose Entity,” where community members form and invest in a business that operates the community solar project. If your participation is limited to investing in the community solar project and you do not participate in the operation of the project on a regular, continuous, and substantial basis, you are constrained in taking advantage of the ITC because you are considered a “passive investor.” IRS rules require that a tax credit associated with a passive investment only be used against passive income tax liability, which only applies to income generated from either a rental activity or a business in which the individual does not materially participate. Many homeowners will therefore not have passive income against which the ITC can be claimed."

How solar+storage Could Protect Multifamily Affordable Housing from Power Outages at little or no net Cost [3] 1. Between $17.9 billion and $23.3 billion of electricity value alone would flow into these communities, if all low-income households went solar.

2. The installation and operation of a full low-income solar build-out would also contribute an additional $18.7 billion of local economic output each year, resulting in roughly 138,376 jobs.

3. The 49.1 million households that earn less than $40,000 of income per year make up 40 percent of all US households but only account for less than 5 percent of solar installations. Lower income households face key barriers that are difficult to overcome.

4. Lower income households are less likely to own their roof due to higher rates of living in multi-family buildings and being renters (49.1 percent of households with incomes less than $40,000 are renters versus 21.8 percent of households with incomes greater than $40,000).

5. Electricity costs account for 5.7 percent of the median low-income family’s budget, while they only account for 1.9 percent for other families.

6. A typical low-income family consumes roughly 10,060 kilowatt-hours of electricity at a cost of $1,272 per year. Other, more affluent families consume roughly 11,720 kilowatt-hours of electricity on average, at a cost of $1,558 per year. Nevertheless, low-income families do use less electricity overall and use only 22 percent of the electricity used in American homes despite accounting for roughly 25 percent of all housing units.

7.The federal government spends billions of dollars each year on energy for low-income households:

  • In fiscal year 2014, the federal government provided states with $3.4 billion through the Low-Income Home Energy Assistance Program (LIHEAP) to assist low-income families with their home energy bills. Historically, these LIHEAP dollars only cover about 15 percent of all eligible low-income households.
  • The U.S. Department of Housing of Urban Development (HUD) expends about $6.3 billion on energy costs each year for federally assisted housing.

PV site suitability analysis using GIS-based spatial fuzzy multi-criteria evaluation (2011)[1]

Abstract -Application of a GIS-based spatial multi-criteria evaluation approach, in terms of the FLOWA module to assess the land suitability for large PV farms implementation in Oman

  • According to IEA, by 2050, PV and Concentrated solar power will be able to generate 9000TWh of electricity
  • GIS and Multi-Criteria Analysis (MCA) together provide a fine lens for the optimal site selection for plants.
  • Overview of GIS base MCA and it's methodology to PV farms siting
  • Classification of various technical (solar radiation, land accessibility, land use), economical(Grid proximity, land slope, load poles) and environmental(sensitive areas, Hydrographi line, sand/dust risk) factors affecting optimum locations for large PV farms
  • Case study of Oman with different PV technology

Geographical Information Systems (GIS) and Multi-Criteria Decision Making (MCDM) methods for the evaluation of solar farms locations: Case study in south-eastern Spain (2013)[2]

Abstract - Combination of a Geographic Information System(GIS) and tools or multi-criteria decision making(MCDM) methods in order to obtain the evaluation of the optimal placement of photovoltaic solar power plants in the area of Cartagena(Region of Murcia),in south east Spain. The use of MCDM the criteria or factors are weighted in order to evaluate potential sites to locate a solar plant. Analysis and calculation of the weights of the factors are conducted using Analytic Hierarchy Process(AHP). The assessment of the alternatives according to their degree of adequacy was carried out through the TOPSIS method (Technique for Order Preference by Similarity to Ideal Solution). .

  • Detailed method for the evaluation of solar farm location.
  • Analysis and calculation of the weight of all relevant factors are conducted using Analytic Hierarchy process (AHP). AHP method was used to determine the importance of the different criteria used in the process.
  • Assessment of the alternatives is carried out through the TOPSIS method (This method ends with the calculation of the relative proximity to the ideal solution of each alternative that will be called Ranking.
  • Main criteria for selection of PV Farm with weight: Location(48.625%), climate(28.562%), Orographical(17.259%),Environmental(5.553%).
  • Complete case study for south-eastern Spain using Geographic Information System(GIS) system with Multi criteria decision making methods (GIS-MCDM).

Solar Power Prediction for Smart Community Microgrid (2016)[3]

Abstract - Microgrids will enable the integration of distributed renewable energy such as roof top solar panels within smart city communities. For microgrids to operate reliably and efficiently, prediction algorithms are important because of the fluctuation of solar energy and its dependence on weather. This paper presents a machine learning based algorithm, which learns a regression tree model with time of the day and humidity as main parameters.This work shows that solar panel prediction in Houston is heavily dependent on humidity of the region.

  • Application of regression tree algorithm for solar power prediction.
  • Various solar energy prediction techniques were discussed like Numeric weather prediction method (NWP), persistence method, Auto regressive Model, Support vector machines, Neural network technique etc.
  • Most Important variable to predict power are humidity, time of the day and sky condition etc.
  • Historical data for various variables for model learning through NOAA(The National Oceanic and Atmospheric Administration) are temperature, humidity, pressure, wind speed and wind direction
  • solar power production is inversely proportional to the humidity.


User-centered design for smart solar-powered micro-grid communities(2014)[4]

Abstract - CoSSMic (Collaborating Smart Solar powered Micro-grids) is an EU funded project aimed at developing a system for smart management and control of solar energy. The system must be relevant to a community of end-users and other stakeholders. Two processes are described to contribute in meeting this aim, user-centered design and lean startup product design. Iterative approach to the design of the system which incorporates these two processes are described.

  • Two feasibility studies are conducted in Konstanz, Germany and the Province of Caserta, Italy. Both trial locations are quite different in terms of population, solar irradiation, available equipment and electrical consumption.
  • Iterative approach with an emphasis on user-centered design and lean startup product design.
  • Establishment of workshops to design the model and strucure.
  • quite successful in building up relations between potential users and the project teams

Neural Network for Estimating Daily Global Solar Radiation Using Temperature, Humidity and Pressure as Unique Climatic Input Variables (2016)[5]

Abstract - A method for estimating daily global solar radiation, combining empirical models and artificial neural networks. The model uses temperature, relative humidity and atmospheric pressure as the only climatic input variables. Neural networks have better accuracy than empirical models and linear regression.

  • Various methods to estimate solar radiation are discussed.
  • Initial estimations are generated using empirical model. Then they are used with temperature, relative humidity and atmospheric pressure as input variables for the neural network to improve estimations
  • This method is useful even in case of absence of data

Feasibility Study for a Solar-Energy Stand-Alone System:(S.E.S.A.S.)(2012)[6]

Abstract - Study to serve a small community living on Stand-Alone Solar-Energy (S.A.S.E.S.) system. As a basis for the study 1 cubic meter of hydrogen is to be produced by electrolysis in 5 hrs that requires energy input of 5 KW-hr. Solar hydrogen production by water electrolysis is described and design parameters are specified.

  • Coupling solar energy with hydrogen production along with fuel cells is the main feature of the S.E.S.A.S.
  • Main components: photovoltaic module, water electrolyzer and fuel cell.
  • Economic feasibility has been carried out
  • More feasible for scale up production

Estimation of Hourly Solar Radiation on Horizontal and Inclined Surfaces in Western Himalayas(2011)[7]

Abstract - Method is used to estimate hourly, global, diffuse solar radiation for horizontal surfaces and total solar radiation on inclined and vertical surfaces at different orientations with greater accuracy for any location.

  • Hourly global & diffuse solar radiation is measured to calculate the direct radiation from the total solar radiation
  • The hourly solar radiation has also been calculated and compared using two methods: 1. Gueymard daily integration

approach from the measured daily solar radiation data & 2. model to estimate global solar radiation using temperature and sunshine hour data has been developed (Chandel et al.) which is used to calculate the hourly solar radiation Data.

  • Total solar radiation on the inclined surfaces and vertical surfaces for different orientations have also been estimated.

Guidebook for community solar programs in Michigan Communities (2014)

  • The Act required Michigan electric providers to ramp up their use of renewable energy in order to obtain 10% of their electricity sales from renewable resources in 2015.
  • Cherryland Electric Cooperative and Traverse City Light & Power, initiators of Michigan’s first Community Solar project.
  • The modeling tools consist of the DOE’s “Systems Analysis Model” (SAM), economic modeling software for renewable energy projects, and the newly created “Michigan Community Solar Analysis Tool”, an Excel spreadsheet-based tool that uses data from the SAM modeling tool to analyze various Community Solar configurations. These tools enable Michigan utilities, businesses, neighborhood associations, citizens’ groups, and others to analyze the financial effects of using various structures and configurations in the development of their projects.
  • Despite having less access to solar radiation than Michigan, Germany is setting the global record for solar power production. Community solar programs need to be accelerated.
  • Michigan-based Dow Chemical Company is currently manufacturing a shingle product, which protects roofs like a standard shingle and contains solar cells that can power a home.
  • The AEPPTE expired on December 31, 2012, leaving the state without a property tax incentive, although there have been several attempts to reintroduce legislation that would continue the exemption and clarify the real versus personal property issue.
  • Michigan does not currently have any solar access laws.
  • For a comprehensive list of resources Appendix III
  • Colorado (followed by Arizona) has the most Community Solar projects.
  • Four main business model :Buy PV power, Lease PV panels, Purchase PV panels, Invest in a PV project

1. Buy PV Power - Two Case studies 1. BRIGHT TUCSON COMMUNITY SOLAR & 2. Sacramento Municipal Utility District (CA)’S SOLARSHARES PROGRAM 2. Lease PV Panels - Cherryland Electric Cooperative – Michigan’s first SUN Alliance Community Solar farm Two case studies- 1. Berea Solar Farms & 2. SUNSHARE – COLORADO SPRINGS UTILITIES 3. Buy PV Panels - Community Solar projects that involve purchasing of PV panels by customers are usually owned by a developer under contract with the local utility. case study - CLEAN ENERGY COLLECTIVE, LLC (CEC) of Carbondale, Colorado.

References

  1. Yassine Charabi, Adel Gastli, PV site suitability analysis using GIS-based spatial fuzzy multi-criteria evaluation, Renewable Energy, Volume 36, Issue 9, September 2011, Pages 2554-2561, ISSN 0960-1481, http://dx.doi.org/10.1016/j.renene.2010.10.037](2011)
  2. Juan M. Sánchez-Lozano, Jerónimo Teruel-Solano, Pedro L. Soto-Elvira, M. Socorro García-Cascales, Geographical Information Systems (GIS) and Multi-Criteria Decision Making (MCDM) methods for the evaluation of solar farms locations: Case study in south-eastern Spain, Renewable and Sustainable Energy Reviews, Volume 24, August 2013, Pages 544-556, ISSN 1364-0321, http://dx.doi.org/10.1016/j.rser.2013.03.019
  3. W. Cabrera, D. Benhaddou and C. Ordonez, "Solar Power Prediction for Smart Community Microgrid," 2016 IEEE International Conference on Smart Computing (SMARTCOMP), St. Louis, MO, 2016, pp. 1-6. doi: 10.1109/SMARTCOMP.2016.7501718
  4. L. W. M. Wienhofen, C. Lindkvist and M. Noebels, "User-centered design for smart solar-powered micro-grid communities," 2014 14th International Conference on Innovations for Community Services (I4CS), Reims, 2014, pp. 39-46. doi: 10.1109/I4CS.2014.6860551
  5. Victor Adrian Jimenez, Amelia Barrionuevo, Adrian Will, Sebastián Rodríguez,"Neural Network for Estimating Daily Global Solar Radiation Using Temperature, Humidity and Pressure as Unique Climatic Input Variables (2016)"
  6. Hussein Abdel-Aal, Mohamed Bassyouni, Maha Abdelkreem, Shereen Abdel-Hamid, Khaled Zohdy,"Feasibility Study for a Solar-Energy Stand-Alone System:(S.E.S.A.S.)(2012)"
  7. Shyam S. Chandel, Rajeev K. Aggarwal,"Estimation of Hourly Solar Radiation on Horizontal and Inclined Surfaces in Western Himalayas(2011)"
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