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Record W1606128843 · doi:10.22004/ag.econ.59701

Managing Water Shortages in the Western Electricity Grids

2010· preprint· en· W1606128843 on OpenAlexaboutno aff
Hugh Scorah, Amy Sopinka, G. Cornelis van Kooten

Bibliographic record

VenueRePEc: Research Papers in Economics · 2010
Typepreprint
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsHydroelectricityElectricityWind powerEnvironmental scienceRenewable energyTonneFossil fuelPumped-storage hydroelectricityVariable renewable energyNatural resource economicsEconomic shortageWater resource managementEnergy storageEconomicsEngineeringDistributed generationWaste management

Abstract

fetched live from OpenAlex

British Columbia’s electricity grid is comprised primarily of hydroelectric generating assets. The ability to store water in reservoirs is a significant advantage for the province allowing it to import from Alberta when prices are favourable. Alberta, has a heavily fossil-fuel based electricity portfolio, but has seen substantial growth in its wind energy capacity. However this variable energy technology impacts the province’s grid operations. Wind energy is both variable and uncertainty. However, wind energy in Alberta can be stored via BC’s reservoir systems. In this paper, we examine the extent that drought impacts the both overall operating costs as well as the cost of reducing CO2 emissions. We model the Alberta and BC interconnected grids varying both the impact of the drought and the transmission capacity between the provinces. We determine that storing wind energy leads to an overall cost reduction and that emission costs are between $20 and $60 per tonne of CO2.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
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 score0.114
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 science0.0010.000
Research integrity0.0010.004
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 head0.267
Teacher spread0.252 · 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.

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
Published2010
Admission routes1
Has abstractyes

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