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Record W3124039149

An Economic and Stakeholder Analysis for the Design of IPP Contracts for Wind Farms

2016· preprint· en· W3124039149 on OpenAlexfundno aff
Şener Salcı, Glenn P. Jenkins

Bibliographic record

VenueRePEc: Research Papers in Economics · 2016
Typepreprint
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsnot available
FundersUniversity of California, Los AngelesLoughborough UniversityImperial College LondonQueen's UniversityUniversity of WarwickGeorge Washington University
KeywordsCape verdeStakeholderBusinessInvestment (military)Government (linguistics)Net present valueYield (engineering)Wind powerFinanceRate of returnPrivate sectorEconomicsEconomyMicroeconomicsEngineeringEconomic growth
DOInot available

Abstract

fetched live from OpenAlex

In this paper we introduce a method for quantifying the benefits and costs of implementing a grid-connected onshore wind project that is owned and operated by an independent power producer (IPP). The proposed policy analysis tool is applied to the appraisal of a wind farm in Santiago Island, Cape Verde. The policy analysis is conducted from the perspectives of the electric utility, the country's economy, the government and the private sector investor. The key question is whether the design of the power purchase agreement (PPA) will yield a high enough rate of return to the project to be bankable, while at the same time yielding a positive net financial and economic present value to the electric utility and the country respectively. The PPA results in a negative outcome for the economy of Cape Verde in almost all circumstances. In contrast the owners of the IPP are guaranteed a very substantial return for their modest investment under all circumstances.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0020.003
Scholarly communication0.0040.006
Open science0.0010.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0110.001

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 head0.054
GPT teacher head0.298
Teacher spread0.244 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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Same venueRePEc: Research Papers in EconomicsSame topicElectric Power System OptimizationFrench-language works237,207