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Record W4407196837 · doi:10.1016/j.energy.2025.134903

Techno-economic opportunities for integration of renewable energy into the Saskatchewan energy system using EnergyPLAN

2025· article· en· W4407196837 on OpenAlex
David Ross-Hopley, S R Rahman, Lord Ugwu, Hussameldin Ibrahim

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEnergy · 2025
Typearticle
Languageen
FieldEngineering
TopicIntegrated Energy Systems Optimization
Canadian institutionsUniversity of CalgaryUniversity of Regina
Fundersnot available
KeywordsRenewable energyEnergy engineeringEnergy (signal processing)Energy systemEnvironmental economicsNatural resource economicsBusinessEconomicsEnvironmental scienceEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

Many renewable energy opportunities exist but scientific gaps remain on the techno-economic feasibility of a transition, especially when systems are considered holistically across all energy sectors. The purpose of this study is to investigate the efficacy of Smart Energy Systems using renewable energy compared to carbon capture and storage technologies. These decarbonization strategies are investigated through a case study in Saskatchewan, Canada. The study uses EnergyPLAN for modelling the energy system and considers the transportation, heating, industrial and electrical sectors. The analysis demonstrates that a Smart Energy System and renewable energy is feasible and preferred based on energy system efficiency, carbon dioxide emissions and costs. A transition has been shown to reduce annual carbon dioxide emissions by 52 % and total annualized system costs by 20 % with further reductions achieved by increasing the capacity for interprovincial trading. • A Smart Energy System in Saskatchewan would make contributions to decarbonization. • The existing Saskatchewan energy system can integrate additional renewable energy. • Interprovincial cooperation can further optimise the energy system. • A reduction in grid stabilizing units enhances renewable energy supply. • A Smart Energy System can reduce CO 2 emissions by 52 % and system costs by 20 %.

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.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.983
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
Bibliometrics0.0010.000
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 head0.015
GPT teacher head0.207
Teacher spread0.192 · 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