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Record W2516161433 · doi:10.1109/pscc.2016.7540832

Integrated energy management system for isolated microgrids

2016· article· en· W2516161433 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceEnergy managementEnergy management systemSystems engineeringEnergy (signal processing)EngineeringPhysics

Abstract

fetched live from OpenAlex

This paper proposes an integrated energy management system (IEMS) for isolated microgrids considering demand response, fossil-fuel-based and renewable-based distributed generators (DGs), and energy storage systems (ESS). In the proposed approach, the unit commitment (UC) and optimal power flow (OPF) constraints are jointly included in the IEMS model, and to account for forecasting errors in renewable generation and electricity demand, a model predictive control (MPC) technique is adopted. The proposed IEMS model is compared with a “standard” decoupled energy management system (DEMS) in which the dispatch problem is decomposed into UC and OPF sub-problems, and the impact of MPC implementation and forecast errors are also analyzed. Both IEMS and DEMS approaches are tested and compared using a modified CIGRE medium voltage benchmark system. The results demonstrate the effectiveness of the proposed IEMS and MPC techniques.

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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.976
Threshold uncertainty score0.242

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.003
GPT teacher head0.154
Teacher spread0.150 · 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

Quick stats

Citations15
Published2016
Admission routes1
Has abstractyes

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