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Record W2983586422 · doi:10.18280/jesa.520412

Techno-Economic Analysis of a Microgrid Hybrid Renewable Energy System in Jordan

2019· article· fr· W2983586422 on OpenAlexvenueno aff
Jamil Al Asfar, Ahmad Atieh, Razan Al-Mbaideen

Bibliographic record

VenueJournal Européen des Systèmes Automatisés · 2019
Typearticle
Languagefr
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsnot available
Fundersnot available
KeywordsMicrogridRenewable energyEconomic analysisEnvironmental economicsNatural resource economicsBusinessEnvironmental scienceEconomicsEngineeringElectrical engineeringAgricultural economics

Abstract

fetched live from OpenAlex

Microgrid is a practical way to integrate conventional and renewable energy sources in small premises.This paper mainly performs a techno-economic analysis of microgrid deployment in Jordan, and analyzes the performance and economic impact of hybrid renewable energy systems for a selected household within the University of Jordan region.Different scenarios were constructed based on the maximum, minimum and average of solar radiation and wind speed data in 2007~2016.In addition, three hybrid renewable energy systems were investigated for the microgrid to the household, namely, (1) photovoltaic generator, wind turbine, diesel generator and battery bank, (2) photovoltaic generator, wind turbine and battery bank, and (3) diesel generator.The comparison shows that the lowest net present cost ($33,547) and lowest electricity cost ($0.237/kWh)were observed in the first hybrid renewable energy system in the scenario of the maximum solar radiation and wind speed.Therefore, the optimal configuration of the hybrid renewable energy system for the microgrid includes: a 1.3kW photovoltaic generator, a 9kW wind turbine, a 1.6kW diesel generator, and a bank of 6 batteries.

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)0.000
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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.221
Teacher spread0.212 · 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

Citations11
Published2019
Admission routes1
Has abstractyes

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Same venueJournal Européen des Systèmes AutomatisésSame topicHybrid Renewable Energy SystemsFrench-language works237,207