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Record W2731558198 · doi:10.55016/ojs/sppp.v9i1.42598

The Challenge of Integrating Renewable Generation in the Alberta Electricity Market

2016· article· en· W2731558198 on OpenAlexaffabout
G. Kent Fellows, Michal C. Moore, Blake Shaffer

Bibliographic record

VenueThe School of Public Policy Publications · 2016
Typearticle
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsRenewable energyElectricity marketElectricityElectricity retailingElectricity generationBusinessNatural resource economicsEnvironmental economicsEconomicsEngineeringElectrical engineeringPower (physics)

Abstract

fetched live from OpenAlex

Renewable electric generation is forecast to enjoy an increasing share of total capacity and supply regimes in the future. Alberta is no exception to this trend, having initiated policy incentives in response to calls for increasing the fraction of wind and solar energy available to the province over the next decade.1 This call is coming from various sectors including advocacy groups, the provincial government and some utilities. The University of Calgary’s School of Public Policy convened a roundtable discussion on Sept. 15, 2015. Given the wide-ranging aspects of increased renewables integration (for example the policy options, economic forces and engineering/technical issues) the topic demands attention from a wide range of experts and stakeholders. To that end, we endeavoured to group expert panellists and representatives of utilities, public agencies, academe and consumer groups to consider the planning necessary to integrate new renewable capacity into the existing and future grid system in the province and its potential impact. The purpose of the roundtable was to facilitate and foster a knowledge exchange between interested and knowledgeable parties while also aggregating this knowledge into a more complete picture of the challenges and potential strategies associated with increased renewables integration in the Alberta electricity grid.

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)0.003
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.977
Threshold uncertainty score0.597

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.022
GPT teacher head0.250
Teacher spread0.228 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2016
Admission routes2
Has abstractyes

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