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Record W4412651215 · doi:10.1016/j.tej.2025.107484

Electricity market design with increasing renewable generation: Lessons from Alberta

2025· article· en· W4412651215 on OpenAlex

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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueThe Electricity Journal · 2025
Typearticle
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsSGS (Canada)University of CalgaryUniversity of Alberta
FundersSocial Sciences and Humanities Research CouncilSocial Sciences and Humanities Research Council of CanadaCanada First Research Excellence FundUniversity of Alberta
KeywordsRenewable energyElectricity marketElectricity generationElectricityElectricity retailingNatural resource economicsBusinessEnvironmental economicsIndustrial organizationEconomicsEngineeringPower (physics)Electrical engineering

Abstract

fetched live from OpenAlex

The electricity sector is going through a period of rapid transition with increasing decarbonization through the growth of renewable energy. In this paper, we consider the case of Alberta which has observed considerable growth in wind and solar generation. We summarize the attributes of Alberta’s simplified electricity market design and examine its challenges with increasing renewable output. We explore lessons from integrated market designs that account for the physical realities of the power system during market clearing, highlighting how this alternative market framework can help alleviate Alberta’s challenges. We note how features of this market design can promote a more reliable and cost-effective grid with increasing renewable energy.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.960
Threshold uncertainty score0.849

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.216
Teacher spread0.204 · 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