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Record W4388620878 · doi:10.1088/2634-4505/ad0c3f

The mid-transition in the electricity sector: impacts of growing wind and solar electricity on generation costs and natural gas generation in Alberta

2023· article· en· W4388620878 on OpenAlexafffundabout
Kristina M E Pearson, Sara Hastings‐Simon

Bibliographic record

VenueEnvironmental Research Infrastructure and Sustainability · 2023
Typearticle
Languageen
FieldEngineering
TopicIntegrated Energy Systems Optimization
Canadian institutionsUniversity of Calgary
FundersAlberta Innovates
KeywordsElectricity generationRenewable energyFossil fuelVariable renewable energyNatural resource economicsElectricityNatural gasWind powerEnvironmental scienceFlexibility (engineering)Environmental economicsEconomicsEngineeringElectric power systemWaste managementPower (physics)

Abstract

fetched live from OpenAlex

Abstract In response to climate change, electricity grids are decreasing their carbon intensity with the addition of wind and solar variable renewable energy generation (VREN). This leads to a mid-transition period, where renewable energy is unable to satisfy electricity demand without contributions from other fossil sources such as natural gas, but also generates sufficiently to constrain conventional generation—changing their operating and market conditions. We use a simplified copper plate model, which scales up and down historical wind and solar generation, to examine how and when the patterns and generation costs for fossil fuel power could change by the increasing capacities of VREN on the relatively isolated Alberta electricity grid. We find that beginning at 20% VREN an increasingly diverse range and reduced hours of dispatched capacity is necessitated from the existing generation. However, even as capacity factors for fossil fuel generation decrease their costs remain reasonable and we found this to be a low-cost pathway for achieving moderate to deep emission reduction goals. A full 86% of demand could be met with VREN before generation costs exceeded 100$/MWh, allowing for an emissions reduction of 28.4–9 million tonnes yr −1 of CO2eq, on a lifecycle basis. In order to integrate the renewable generation, new and existing fossil fuel units will require market rules that incentivise flexibility and ensure they remain in place throughout the transitionary period as they are crucial to balance variable renewable generation.

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)0.002
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: Empirical
Teacher disagreement score0.277
Threshold uncertainty score0.395

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.001
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 head0.007
GPT teacher head0.241
Teacher spread0.234 · 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 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

Citations2
Published2023
Admission routes3
Has abstractyes

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