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Record W4379795209 · doi:10.23977/jeeem.2023.060307

Study on complementary power generation mode of solar thermal and coal-fired power stations under the background of new energy

2023· article· en· W4379795209 on OpenAlexvenueno aff
Yanting Shi

Bibliographic record

VenueJournal of Electrotechnology Electrical Engineering and Management · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced Power Generation Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsPower stationElectricity generationEnvironmental scienceThermal power stationBase load power plantSteam turbineThermal energy storagePower (physics)Solar energySolar powerCoalAutomotive engineeringEngineeringRenewable energyElectrical engineeringDistributed generationWaste managementMechanical engineeringThermodynamics

Abstract

fetched live from OpenAlex

Under the background of new energy, the complementarity of solar energy and coal-fired power plants can increase power output without increasing the thermal load of boilers and systems, which can significantly improve the operation economy of coal-fired power plants. Based on the established complementary power generation analysis model of solar thermal power station and coal-fired power station, the operation modes of light field and energy storage part of demonstration power station with energy storage system are studied under typical meteorological conditions and load conditions. For 100%THA condition, the heat consumption rate of steam turbine generator set decreased by 4.71%.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.017
GPT teacher head0.252
Teacher spread0.235 · 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 source (direct Gemma or distilled Codex), 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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