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Record W4386802698 · doi:10.23977/jeeem.2023.060408

Research on Voltage Control Strategy of DC Microgrid System

2023· article· en· W4386802698 on OpenAlexvenueno aff
San Li, Yutong Shi

Bibliographic record

VenueJournal of Electrotechnology Electrical Engineering and Management · 2023
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsMicrogridPhotovoltaic systemEnergy storageComputer scienceVoltagePower (physics)EngineeringAutomotive engineeringControl engineeringElectrical engineering

Abstract

fetched live from OpenAlex

New energy sources such as solar energy, tidal energy, and geothermal energy possess characteristics of random dispersion, making centralized utilization unfeasible. Microgrid structures and control methods are relatively simple, enabling rational utilization of new energy sources, and have garnered widespread attention. Compared to AC microgrids, DC microgrids are easier to control, reduce energy conversion steps, eliminate factors like reactive power, and maintain frequency consistency. Thus, they are more conducive to the efficient utilization and coordinated control of new energy. This paper investigates the coordinated control strategy of a photovoltaic and energy storage-based DC microgrid system. By assessing the range of bus voltage and the power balance between photovoltaic output and load absorption within the system, a coordinated operational approach for the photovoltaic-energy storage DC microgrid is proposed. Segregating the system into various operating states based on different control methods for photovoltaic units and energy storage, the system's operation becomes more efficient and economical. This further validates the feasibility of the proposed strategy.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.340
Threshold uncertainty score0.537

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.227
Teacher spread0.219 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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