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Research on the High Proportion Consumption Mechanism of New Energy to Promote the Green and Low-Carbon Transformation of Energy

2023· article· en· W4389888616 on OpenAlexaff
Zhen Hu, Ding Wang, Mao Li, Yihan Wu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsInternational Development Research Centre
Fundersnot available
KeywordsEnergy storageComputer scienceRenewable energyEnergy consumptionIntermittent energy sourceElectric power systemPower (physics)Electrical engineeringDistributed generationEngineering

Abstract

fetched live from OpenAlex

For the background that the traditional units have been unable to meet the frequency modulation requirements of the power system with high renewable energy permeability, the energy storage technology with accurate and fast power tracking performance has been widely concerned in the current frequency modulation research field. The fast response and accurate power command tracking characteristics of the energy storage technology make it more suitable than the traditional synchronous unit to participate in the power grid frequency modulation control with high climbing rate and low power demand, which can better meet the system frequency modulation index. it can also significantly reduce the rotating reserve capacity of the power grid. According to the technical parameters of all kinds of energy storage which are widely used at present, it can be known that all types of energy storage can meet the requirements of power climbing rate and response time of frequency modulation in power grid. However, considering that the installation and maintenance cost of energy storage is still at a high level, the application of energy storage alone in FM is still restricted by its high configuration cost, which economically limits its participation in power FM control applications. Therefore, in order to face all kinds of problems existing in the power system with high proportion of new energy, the specific application strategies of energy storage are put forward.

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: Empirical
Teacher disagreement score0.545
Threshold uncertainty score0.158

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 head0.025
GPT teacher head0.242
Teacher spread0.218 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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