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Record W4405107916 · doi:10.3390/engproc2024076094

Review of Techno-Economic Analysis Studies Using HOMER Pro Software

2024· article· en· W4405107916 on OpenAlexaff
David Ross-Hopley, Lord Ugwu, Hussameldin Ibrahim

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsRenewable energyEnvironmental economicsEconomic analysisSoftwareGlobeEngineeringNatural resource economicsComputer scienceEconomicsAgricultural economicsElectrical engineering

Abstract

fetched live from OpenAlex

With decreases in cost accompanying advances in technology, renewable energy is becoming increasingly viable. Much software is available for the techno-economic analysis of energy systems, and HOMER Pro software is frequently applied for micro-grid and industrial analysis. Around the globe, techno-economic analyses of a variety of renewable energy systems have been undertaken using HOMER Pro Version 3.16.0. This study reviews the primary techno-economic findings of past research to investigate recent trends. Based on high-level trendline analysis, it appears that the costs of renewable energy systems have decreased in academic HOMER Pro-based literature. Of the articles analyzed, the LCOEs for 100% renewable energy systems have decreased from $0.91/kWh to $0.70/kWh, while the LCOEs for 0% renewable energy systems have increased from $0.74/kWh to $0.78/kWh.

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 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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.841
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.049
GPT teacher head0.333
Teacher spread0.285 · 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 teacher head, not a consensus.

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

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

Citations9
Published2024
Admission routes1
Has abstractyes

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