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Record W2553557427 · doi:10.1049/cp.2016.0476

Economic viability of price arbitrage operation of vanadium redox battey in Alberta's energy market

2016· article· en· W2553557427 on OpenAlexaboutno aff
Abiola I. Adebayo, Payam Zamani-Dehkordi, Hamidreza Zareipour, Andrew M. Knight

Bibliographic record

Venue12th IET International Conference on AC and DC Power Transmission (ACDC 2016) · 2016
Typearticle
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsVanadiumArbitrageRedoxEnergy (signal processing)BusinessEconomicsMaterials scienceFinanceMetallurgyMathematics

Abstract

fetched live from OpenAlex

With the rising need for energy storage facilities in power systems of various jurisdictions, it is imperative to investigate the profitability of operating energy storage facilities. This paper assesses the economic viability of a transmission-connected Vanadium Redox Battery (VRB). The system under consideration has a power rating that is large enough that the impacts of its operation on the pool price in the Alberta electricity market should be considered. Using 5 year historical price data, we run a self-scheduling mixed integer linear programming (MILP) optimization model to estimate the maximum possible operational profit operating in Alberta's “Energy Only” market. The rate of return on the investment considering 2011 capital cost estimate and forecasted 2020 cost estimate are calculated, based on the simulated cash flow. The predicted ROI is shown to vary significantly depending on the window chosen as “typical” cash flow.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.824
Threshold uncertainty score0.349

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.212
Teacher spread0.206 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2016
Admission routes1
Has abstractyes

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