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Record W2136719147 · doi:10.1260/0144-5987.30.4.533

Technical and Economic Assessment of Hybrid Energy Systems in South-West Nigeria

2012· article· en· W2136719147 on OpenAlexaff
Muyiwa S. Adaramola, Olanrewaju M. Oyewola, S. S. Paul

Bibliographic record

VenueEnergy Exploration & Exploitation · 2012
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsUniversity of Manitoba
FundersNational Renewable Energy Laboratory
KeywordsDiesel generatorHybrid systemRenewable energyPhotovoltaic systemEnvironmental scienceElectricityWind powerStand-alone power systemHybrid powerAutomotive engineeringElectricity generationDiesel fuelEngineeringEnvironmental economicsElectrical engineeringDistributed generationComputer sciencePower (physics)Economics

Abstract

fetched live from OpenAlex

The technical and economic assessment of using hybrid energy system for electricity generation in rural communities in the south-west of Nigeria is investigated in this study. Renewable resources (wind and solar data) in Ibadan located on the latitude of 7.43 °N and longitude 3.91 °E are used. Hybrid Optimization Model for Electric Renewable software has been employed to carry out the present study. It was found that Wind-PV-Generator-Battery hybrid system is most suitable option as stand-alone electricity generating system in Ibadan. The optimal simulation results indicate that the levelised cost of energy for this hybrid energy system varies between $0.437/kWh and $0.606/kWh depending on the diesel price. These costs are significantly lower than the cost of using diesel generator only (without battery) which varies between $0.607 and $0.940 per kWh. It was further observed that there is a significant reduction in emission produced if hybrid energy system is used instead of only generator based energy system. The most suitable hybrid systems in other locations in southwest Nigeria can be identified from the optimal energy system plots provided.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.023
GPT teacher head0.260
Teacher spread0.237 · 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

Citations43
Published2012
Admission routes1
Has abstractyes

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