MétaCan
Menu
Back to cohort
Record W2127306742 · doi:10.1109/pes.2010.5590140

Microgrid economic optimal operation of the combined heat and power system with renewable energy

2010· article· en· W2127306742 on OpenAlexaff
Wei Gu, Zhi Wu, Xiaodong Yuan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicPower Systems and Renewable Energy
Canadian institutionsMinistry of Education and Child Care
Fundersnot available
KeywordsCogenerationMicrogridRenewable energyElectricityElectric power systemElectricity generationStand-alone power systemWind powerAutomotive engineeringEngineeringDistributed generationPower (physics)Electrical engineering

Abstract

fetched live from OpenAlex

Combined heat and power system (CHP) with renewable energy generation, which operates with high efficiency and low costs, is an important form of microgrid. This paper deals with the problem of economic operation of cogeneration system including wind energy, PV, heat recovery boiler and battery. On the basis of predicting the next 24-hours' wind energy and PV power, power and heat demand, a nonlinear optimal model is built to deal with the economic operation of available power resources and formulate the 24-hours' work schedule. Besides, this paper focuses on the effect of battery and peak-valley electricity price on system operation costs. Four different cases with a test CHP system are compared. Test results indicate that peak-valley electricity price would increase the system operating costs, while using battery and peak load shifting can effectively reduce operating costs.

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)0.001
metaresearch head score (Gemma)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.003
GPT teacher head0.170
Teacher spread0.167 · 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

Citations102
Published2010
Admission routes1
Has abstractyes

Explore more

Same topicPower Systems and Renewable EnergyFrench-language works237,207