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Record W4399563140 · doi:10.1109/tpwrs.2024.3413299

Economic Power-Sharing and Stability Enhancement for Virtual Synchronous Generators in Islanded MG

2024· article· en· W4399563140 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 · 2024
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsUniversity of Alberta
FundersKhalifa University of Science, Technology and Research
KeywordsElectric power systemStability (learning theory)Power (physics)Power sharingComputer scienceControl theory (sociology)Economic dispatchElectricity generationAC powerControl engineeringEngineeringElectrical engineeringVoltageControl (management)Physics

Abstract

fetched live from OpenAlex

Dispatchable inverter-based distributed generators can share their power economically in islanded microgrids (MGs) using cost-based droop schemes. However, incorporating cost function into the droop adversely affects the MG stability, and since the main limitation of droop is the lack of inertia provision, a high rate of change of frequency (RoCoF) following a frequency event arises. To address these aspects, this paper proposes a novel control structure for the virtual synchronous generator (VSG) that emulates inertia to mitigate the RoCoF, enhance the MG marginal stability, and preserve decentralized economic power-sharing. The proposed economic dispatch-based VSG (ED-VSG) operates as a cost-based droop during steady-state and a VSG during disturbances. An improved version of ED-VSG is proposed by adding a zero to the transfer function of the ED-VSG to increase the MG stability margin further. A comprehensive evaluation framework has been employed to show the efficacy of the proposed control. Sensitivity analyses have been performed on the MG eigenvalues, considering parameter variations. Consequently, numerical simulations for small and large-scale systems and a lab-scale experimental MG setup show that the proposed controller optimally manages the MG. Furthermore, the results reveal a significant reduction in the maximum RoCoF, highlighting a commendable alignment with stability-oriented 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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.759
Threshold uncertainty score0.651

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 head0.007
GPT teacher head0.203
Teacher spread0.197 · 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