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Record W2971294686 · doi:10.1515/ijeeps-2017-0238

Smart Demand Response Management of Islanded Microgrid using Voltage-Current Droop Mechanism

2018· article· en· W2971294686 on OpenAlex
Sumit Kumar Jha, Deepak Kumar, Innocent Kamwa

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

VenueInternational Journal of Emerging Electric Power Systems · 2018
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsHydro-Québec
Fundersnot available
KeywordsMicrogridVoltage droopVoltagePhotovoltaic systemControl theory (sociology)Computer scienceAC powerMATLABPower (physics)RipplePower managementBoost converterAutomotive engineeringEngineeringElectrical engineeringVoltage sourceControl (management)

Abstract

fetched live from OpenAlex

Abstract The reduction of power of the autonomous microgrid is proposed in this paper. The concept utilized is Conservative Voltage Reduction (CVR). The active and reactive power consumption of the microgrid decreases and a power reserve of the system increased. The voltage–current droop mechanism is used to lessen the voltage of the DG and it reduces the consumption of power on the consumer side. This reduced power is used to cater more demands. The control strategy is used to cater the greater number of loads at the time of power shortage. The DG taken in this paper is photovoltaic (PV) system and perturb & observe MPPT is used. The interleaved boost converter is used as DC- DC converter as it lessens the ripple of the output voltage and inputs current. The simulation is done on MATLAB platform and results are validated at different loading conditions and comparison has been done with P-f/Q-V mechanism.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.775
Threshold uncertainty score0.575

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.008
GPT teacher head0.248
Teacher spread0.239 · 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