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Record W1983601351 · doi:10.1109/tsg.2014.2320954

A Dynamic Mechanism for Wholesale Energy Market: Stability and Robustness

2014· article· en· W1983601351 on OpenAlexaff
Arman Kiani Bejestani, Anuradha M. Annaswamy

Bibliographic record

VenueIEEE Transactions on Smart Grid · 2014
Typearticle
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsAlberta Energy
Fundersnot available
KeywordsRobustness (evolution)Electricity marketRenewable energyDemand responseEnergy marketDynamic pricingElectric power systemEconomicsWind powerPower marketStability (learning theory)MicroeconomicsComputer scienceElectricityPower (physics)Engineering

Abstract

fetched live from OpenAlex

In this paper, a dynamic model of the wholesale energy market that captures the effect of uncertainties of renewable energy sources and real-time pricing with demand response is derived. Beginning with a framework that includes real-time pricing as an underlying state, an attempt is made in this model to capture the dynamic interactions between generation, demand, locational marginal price (LMP), and congestion price near the equilibrium of the optimal dispatch. Conditions under which stability of the market can be guaranteed are derived. Modeling the effect of renewable energy resources (RERs) and demand response as perturbations, robust stability of the energy market model in the presence of such perturbations is discussed. Numerical studies of an IEEE 30-bus are reported to illustrate the effect of transmission lines constraints on the wholesale market stability in the presence of wind power.

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)0.004
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: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.186
Teacher spread0.180 · 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

Citations38
Published2014
Admission routes1
Has abstractyes

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