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Record W4409501920 · doi:10.1049/icp.2025.1140

Optimizing renewable energy integration: a hybrid energy system approach for residential applications

2025· article· en· W4409501920 on OpenAlexaff
Asjad Ali, Asma Bibi, Noor Izzri Abdul Wahab, Muhammad Nadeem Akram, Hafiz Abdul Muqeet, Rizwan A. Farade

Bibliographic record

VenueIET conference proceedings. · 2025
Typearticle
Languageen
FieldEngineering
TopicIntegrated Energy Systems Optimization
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsRenewable energyEnergy (signal processing)Energy systemComputer scienceEnvironmental scienceEnvironmental economicsEngineeringElectrical engineeringEconomicsPhysics

Abstract

fetched live from OpenAlex

Climate change, soaring inflation and energy shortages are driving interest in Distributed Energy Sources (DES), especially in developing countries like Pakistan, where power outages disrupt daily life. Residential communities are increasingly adopting renewable energy sources (RES) and battery storage systems (BESS) to reduce reliance on utility grid and produce cheap energy compared to grid. The authors propose a hybrid energy system (HES) combining solar PV, a diesel generator, and BESS to reduce levelised cost of energy (LCOE) and emissions while addressing energy outages for a residential building in Lahore, Pakistan. The average daily utilization of selected building is around 463 kWh/day with a peak demand of 33 kW. Different configurations are designed and their techno-economic and environmental analysis is conducted using HOMER Software. In one scenario combining PV-DG-BESS-Grid, the lowest LCOE of $0.0120 was achieved, but it resulted in higher emissions due to DG dependence. A PV-BESS-Grid configuration had a slightly higher LCOE of $0.0124 but significantly lower emissions. Sensitivity analysis also revealed that PV-BESS-Grid system to be most robust among all the designed systems.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.944
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.010
GPT teacher head0.207
Teacher spread0.197 · 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.

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
Published2025
Admission routes1
Has abstractyes

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