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Record W2904015948 · doi:10.1109/icrera.2018.8566801

Cooperative Control and Power Management for Islanded Residential Microgrids with Local Phase-wise Generation and Storage Units

2018· article· en· W2904015948 on OpenAlexaff
S. A. Raza Naqvi, Jin Jiang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsWestern University
Fundersnot available
KeywordsVoltage droopConvertersPower (physics)Control theory (sociology)Power managementComputer scienceThree-phasePower BalancePower controlVoltageMicrogridControl (management)Phase (matter)AC powerControl engineeringEngineeringElectrical engineeringVoltage source

Abstract

fetched live from OpenAlex

A cooperative control and management strategy for islanded residential microgrids is presented in this paper. In addition to the loads, PV generation and battery storage are considered within each phase using droop control schemes. The proposed strategy uses a two-tiered management scheme to coordinate intraand inter-phase power management. Each intraphase control relies on a modified vector control with a multisegment (P/f) droop strategy to balance the generation, load and potential power transfer among other two phases. The inter-phase management only comes into play when there is an imbalance among phases so that desirable power can be transferred to the phases with deficiencies. This is accomplished by back-toback converters connecting the phases. PSCAD/EMTDC has been used to investigate the performance of the proposed strategy. It is interesting to observe that when extra power is needed in one particular phase, the desired amount is transferred through the back-to-back converters from other phases. As a result, the balance for voltage, frequency, and power can be achieved at both the phase level and the system level.

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.

How this classification was reachedexpand

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.875
Threshold uncertainty score0.391

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 head0.006
GPT teacher head0.204
Teacher spread0.198 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2018
Admission routes1
Has abstractyes

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