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DC Optimal Power Flow of the PJM Five-Bus System Using General Algebraic Modeling System (GAMS)

2025· article· W7154574186 on OpenAlexaff
Pierre O. Dorile, Daniel R. Jagessar, Jacky Petit-Homme

Bibliographic record

Venuenot available
Typearticle
Language
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsIndependent Electricity System Operator
Fundersnot available
KeywordsControl theory (sociology)Power flowFlow (mathematics)Systems modelingAlgebraic numberElectric power system

Abstract

fetched live from OpenAlex

This paper presents a practical application of the Direct Current Optimal Power Flow (DC-OPF) model to the PJM 5-bus test system using the General Algebraic Modeling System (GAMS). The study aims to minimize system generation costs while respecting generator capacity, load balancing, and transmission line constraints through utilizing a linear programming approach for computational efficiency, but also ensuring reliability and operational efficiency. Key operational outcomes such as generator dispatch, power flows, and Locational Marginal Prices (LMP) are analyzed, with observed LMPs ranging from $ 10/MWh to $ 40/Wh depending on system congestion. The results highlight the impact of transmission congestion, notably identifying line E-D as the limiting element affecting market prices. Through comparison of AC power flow, the strengths and limitations of DC-OPF is showcased, particularly its inability to model voltage magnitudes and reactive power. The findings highlight the values of DC-OPF for fast market clearing applications while emphasizing the need for AC analyses in certain scenarios that may be sensitive to voltage and reactive power. The study provides actionable information for system operators and researchers engaged in the design and operational planning of the electricity market.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.779
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.006
GPT teacher head0.191
Teacher spread0.185 · 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
Published2025
Admission routes1
Has abstractyes

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