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Record W2153618882 · doi:10.1109/tpwrs.2009.2039652

Application of a Joint Deterministic-Probabilistic Criterion to Wind Integrated Bulk Power System Planning

2010· article· en· W2153618882 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 · 2010
Typearticle
Languageen
FieldEngineering
TopicPower System Reliability and Maintenance
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsProbabilistic logicElectric power systemWind powerReliability engineeringReliability (semiconductor)Mathematical optimizationComputer scienceEngineeringOperations researchPower (physics)MathematicsElectrical engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

The basic objective of bulk power system planning is to develop the system as economically as possible while maintaining an acceptable level of service reliability. The traditional methods used by system planners to maintain acceptable bulk power system reliability are challenged in the present move to incorporate higher wind power penetration levels. Combining deterministic considerations with probabilistic assessment in order to evaluate the quantitative system risk and conduct bulk power system planning has therefore become increasingly necessary and important in recent years. This paper examines the capacity value of wind generation using various approaches and the utilization of this value under the deterministic N-1 criterion. The application of a joint deterministic-probabilistic criterion for bulk system expansion planning in wind integrated systems is presented. The application of the conventional deterministic N-1, the basic probabilistic and the joint deterministic-probabilistic criteria is illustrated in a wind integrated test system in this paper.

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 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 score0.808
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.010
GPT teacher head0.220
Teacher spread0.210 · 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