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Record W7117584470 · doi:10.1016/j.asej.2025.103946

Economic feasibility of solar and wind energy harvesting in Karbala, Iraq

2025· article· en· W7117584470 on OpenAlexaff
Intisar R. Saleh, B. Rafiei, K. Gharali, B. Sajadi

Bibliographic record

VenueAin Shams Engineering Journal · 2025
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPayback periodPhotovoltaic systemInternal rate of returnRenewable energyNet present valueWind powerTariffElectricityInvestment (military)Capital cost

Abstract

fetched live from OpenAlex

This study discusses the economic feasibility of investment in renewable energy comparing wind turbines (WT) and photovoltaic (PV) technology. Nine scenarios were compared according to economic indices namely Net Present Value (NPV), Payback Period (PBP), and Internal Rate of Return (IRR) using parameters like power efficiency, capital cost, and electricity tariff. By incorporating a 20 kW battery storage system to support night-time demand, and considering current market rates for investment, operation, and maintenance alongside local and international electricity tariffs, the study concludes that at an international electricity price of $0.10/kWh, wind turbine (WT) systems achieve an NPV of $43,674—approximately 1.5 times higher than that of photovoltaic (PV) systems ($28,764.5). In addition, the IRR for WT and PV were found to be 15.2 % and 16.7 %, respectively, suggesting that both technologies can be financially viable given favourable tariffs. The need for tariff reform, cost reduction, and efficiency enhancement to release renewable energy investment in Iraq is emphasized by these findings.

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)0.002
metaresearch head score (Gemma)0.002
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.008
GPT teacher head0.219
Teacher spread0.210 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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