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Record W2795310188 · doi:10.1049/pbpo130e_ch4

Financing for community wind and solar project development

2018· book-chapter· en· W2795310188 on OpenAlex
Lindsay Miller, Rupp Carriveau

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInstitution of Engineering and Technology eBooks · 2018
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSocial Acceptance of Renewable Energy
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsRenewable energyWind powerLeaseBusinessEnvironmental economicsFinanceCapital costInvestment (military)Natural resource economicsEconomicsEngineeringPolitical science

Abstract

fetched live from OpenAlex

Community energy, and in particular, community wind and solar, has experienced significant growth in recent years. The main challenge to further expansion and implementation of community renewable energy projects is the high capital costs associated with project development. This chapter will present case studies of community wind and solar financing and include innovative mechanisms such as lease financing, sales of renewable energy credits, crowdfunding, and unconventional loan strategies. Through compilation of these cases, the objective is to provide prospective small renewable energy developers options as to how they can go about financing their projects and ultimately empower communities to independently produce energy while reducing greenhouse gases. Community energy, in particular, community wind and solar, has experienced significant growth in recent years. Driving this trend is the desire for communities to become energy self-sufficient and more environmentally conscious. Benefits of community wind and solar extend to include increasing community capacity, empowering residents, and promoting energy efficiency and conservation. The main challenge for further expansion and implementation of community renewable energy projects is the high capital costs associated with project development. With initial costs representing approximately 70 percent of the life cycle costs of the project [1], it can take several years to recoup this investment and can impede the ability of local developers to raise enough capital. Small utility-scale wind power projects have provided proving grounds for new technology and innovative financing structures. Historically, financing of community wind projects has generated innovative structures that were later adopted by the broader wind market and are now popular mainstream financing structures, such as the special allocation partnership flip structure [2]. More recently, community wind projects have been financed with creative structures that capitalize on incentives and make use of public market capital. Community solar is a popular community energy choice due to the scalability of projects. Small communities and neighbourhoods can pursue solar energy more easily by selecting the number of panels required to suit their needs. Community solar has relied on three main financing structures: utility-sponsored, special-purpose entity, and non-profit, to implement projects of various scales and make use of available incentives. Despite many community wind and solar projects achieving financing success, there are challenges in replicating the elements of some of these deals. Some of the cases only work in the exact circumstance presented due to specific incentive availability or legalities in different areas. Also, since these proposed structures are new to the industry, transaction costs may be high due to the learning process of executing these deals and development of the financing package could be lengthy for the same reason. This chapter will present case studies of community wind and solar financing and include innovative mechanisms such as lease financing, sales of renewable energy credits, crowdfunding, and unconventional loan strategies. Through compilation of these cases, the objective is to provide prospective small renewable energy developers options as to how they can go about financing their projects and ultimately empower communities to independently produce energy while reducing greenhouse gases. These examples serve as encouraging case studies for other community projects looking for ways to raise capital and make use of programmes and incentives to piece together a financial package. Furthermore, the cases presented have the potential to extend beyond community projects to commercially renewable energy project finance.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.974
Threshold uncertainty score0.708

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.254
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it