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Record W4200257332 · doi:10.52013/2713-3052-44-4-5

ESTIMATION OF THE ECONOMIC EFFICIENCY OF AN INVESTMENT PROJECT FOR THE INTRODUCTION OF SOLAR PANELS IN BUILDINGS OF AN ADMINISTRATIVE QUARTER IN THE MUNICIPALITY OF PLATEAU (CÔTE D’IVOIRE)

2021· article· en· W4200257332 on OpenAlexaboutno aff
Мария Лавровна Горбунова, Yao Donatien Kouassi

Bibliographic record

VenueGlobus economy sciences · 2021
Typearticle
Languageen
FieldEnergy
TopicPhotovoltaic System Optimization Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsPayback periodEnvironmental economicsDepreciation (economics)Investment (military)Renewable energySolar powerQuarter (Canadian coin)Internal rate of returnBusinessSolar energyBenefit–cost ratioEconomicsEngineeringProduction (economics)Power (physics)Economic growthGeographyElectrical engineeringMicroeconomics

Abstract

fetched live from OpenAlex

The use of renewable energy sources is a topical direction in the development of the energy industry in the modern world. However, when investing, choosing the optimal strategy is essential to keep costs down. The goal is to evaluate the efficiency of using solar panels parallel to the electric grid for the plateau municipality, the Republic of Cote d’Ivoire. The objectives of the study in this regard are to determine the strategy to the greatest extent, affecting the reduction of the investment cost when introducing a solar battery project, the calculation of economic indicators that allow us to assess the risks when making decisions to implement the investment. For the assessment, a technique is presented that differs from the existing complex taking into account specific indicators (average annual insolation, efficiency of solar panels, temperature coefficient, price of 1 M ^ 2 solar panels, transportation costs, cost of installation work, depreciation period, maintenance costs, property tax, the cost of training employees. The methodology includes the author’s recommendations, taking into account the specific features of determining the indicators of the annual economic effect, NPV. IRR, DPP for a solar battery project. A comparative analysis of an autonomous SES and operating in parallel with the electric grid. Conclusions: SES in parallel with a network of solar power plants. reduces the cost of the project investment, and also hinders the payback period of the project.

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)0.003
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.728
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.041
GPT teacher head0.315
Teacher spread0.274 · 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
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
Published2021
Admission routes1
Has abstractyes

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