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Record W7001357742

Integration of a Solar Energy System at the Future Building Laboratory of Concordia University: Simulation, Analysis, and Testing of Different Operational Modes.

2025· other· en· W7001357742 on OpenAlexaboutno aff

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsBackupPhotovoltaic systemRenewable energyFlexibility (engineering)Rural electrificationElectric power systemElectrificationSystem integrationSolar energy
DOInot available

Abstract

fetched live from OpenAlex

This research explores the development and integration of a solar photovoltaic (PV) system and a vehicle-to-home (V2H) backup power system at the Future Building Laboratory (FBL) of Concordia University, Montreal, Quebec. The study addresses the challenges of rural electrification, proposing renewable energy systems as sustainable and eco-friendly solutions for off-grid applications. A modified electrical power system is designed for the FBL, incorporating critical loads, a subpanel, manual transfer switches, grid-forming and grid-following converters, battery storage, and an electric vehicle with a vehicle-to-home inverter. The system's performance is analyzed through simulation and experimental testing. Sunny Island (grid-forming/battery charger) and Sunny Boy (grid-following) were simulated in both standalone and grid-connected scenarios, with control strategies ensuring seamless operation in grid-forming and grid-following modes. Experimental results validate the simulations, demonstrating consistent performance of the converters under different operating conditions, including parallel operation. The research also explores vehicle-to-load (V2L) and vehicle-to-home (V2H) systems, highlighting the capability of EVs to serve as reliable emergency backup power sources. The experimental results demonstrate that integrating V2H technology with renewable energy systems enhances the overall resiliency and flexibility of decentralized power systems. Moreover, this EV to-home integration reduces reliance on traditional backup energy sources, thereby enhancing sustainability. Thus, this study provides a comprehensive framework for integrating solar PV power and EV technologies into decentralized power systems, demonstrating their potential to create scalable, reliable, and environmentally sustainable solutions for rural and remote electrification needs.

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)0.000
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 score0.158
Threshold uncertainty score0.314

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.257
Teacher spread0.241 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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