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Record W2162703984 · doi:10.1109/psce.2009.4840193

A novel approach to disco planning in electricity markets: Mathematical model

2009· article· en· W2162703984 on OpenAlexaff
Ayed A. S. Algarni, Kankar Bhattacharya

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsElectricityElectricity marketVariety (cybernetics)Computer scienceCapacity planningWork (physics)Function (biology)Power flowService (business)Term (time)Operations researchElectric power systemPower (physics)Environmental economicsBusinessEconomicsEngineeringElectrical engineeringMarketing

Abstract

fetched live from OpenAlex

A novel approach to address the disco planning issues in a competitive electricity market environment is presented in this paper. Since there exists a variety of electricity markets and associated products and services (i.e. energy markets, ancillary service markets, etc.) which work in different time-frames, the mathematical model presented here uses the AC power flow, and the planning problem is a dynamic model, formulated to tackle all these issues simultaneously. The effects of DG injections on the distribution network, both in the short-term operations (impact on losses) and in long-term planning (impact on feeder capacity) is combined together and mathematically formulated within a comprehensive objective function for planning. Novel goodness factors accounting for DG contribution to system loss reductions and deferment in feeder capacity upgrades are formulated as monetary values.

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)0.002
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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.014
GPT teacher head0.226
Teacher spread0.211 · 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

Citations8
Published2009
Admission routes1
Has abstractyes

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