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Record W2117181535 · doi:10.1109/tpwrs.2004.825823

Assessment of Transmission Congestion Cost and Locational Marginal Pricing in a Competitive Electricity Market

2004· article· en· W2117181535 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Power Systems · 2004
Typearticle
Languageen
FieldEngineering
TopicElectric Power System Optimization
Canadian institutionsHydro One (Canada)
Fundersnot available
KeywordsComputer scienceElectricity marketTransmission (telecommunications)Electric power transmissionReliability (semiconductor)Transmission systemMarginal costTransmission networkNetwork topologyPower system simulationElectric power systemReliability engineeringElectricityNetwork congestionComputer networkEngineeringPower (physics)TelecommunicationsEconomicsElectrical engineering

Abstract

fetched live from OpenAlex

In an open-access environment, transmission constraints can result in different energy prices throughout the network. These prices are, in fact, dependent on a number of factors such as the generating unit bid, system load level, network topology and security limits imposed on the transmission network due to thermal, and voltage and stability considerations. Computing these energy prices at all buses in large transmission networks under given system operating conditions can be time-consuming. This paper describes a simple methodology based on the analysis performed by the Hydro One in-house computer program (PROCOSE) to calculate, for a given period of time, transmission congestion cost (TCC) in dollars per unit time and locational marginal pricing (LMP) in dollars per megawatt-hour (MWh) at any selected bus in the transmission system. In addition, the information provided by the program output on congested transmission elements is used to identify buses in the network whose LMPs are representative of the entire network. The computed LMPs at these buses are used to define zones in the network where each zone has its LMP. The proposed methodology can be used to carry out sensitivity studies to determine the impact of changes in system parameters and operating conditions on the LMPs. The proposed method is illustrated using the IEEE Reliability Test System (RTS) and the Hydro One network system.

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.

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 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 score0.979
Threshold uncertainty score0.814

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.224
Teacher spread0.217 · 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