MétaCan
Menu
Back to cohort
Record W4235181691 · doi:10.1002/9781119283362.ch4

Energy Hub Modeling and Optimization‐Based Operation Strategy for <scp>CCHP</scp> Systems

2017· other· en· W4235181691 on OpenAlexaff
Yang Shi, Mingxi Liu, Fang Fang

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEngineering
TopicIntegrated Energy Systems Optimization
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsSequential quadratic programmingEnergy (signal processing)Mathematical optimizationPower (physics)ElectricityEnergy flowEngineeringMatrix (chemical analysis)Electric power systemCogenerationQuadratic programmingComputer scienceControl engineeringElectricity generationElectrical engineeringMathematics

Abstract

fetched live from OpenAlex

The combined cooling, heating, and power (CCHP) system is the connection between the energy input, that is, the electricity and the fuel, and the building users' demand. A CCHP system can be viewed as an energy hub with multiple energy vectors at the input and output terminals. The energy hub represents an interface between different energy infrastructures and/or loads. This chapter describes the matrix modeling approach for the CCHP system, which includes the components' efficiency matrices modeling, dispatch factors definitions and system conversion matrix modeling. It presents a case study that shows the effectiveness and economic efficiency of the proposed optimal power flow and operation strategy. The chapter adopts the line search method to enable two sequential quadratic programming (SQP) algorithms to converge with arbitrary initial points. The optimization of the overall CCHP system needs to fulfill the three aspects: optimization of the dispatch factors, input energy and power generation unit (PGU) capacity.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.602
Threshold uncertainty score1.000

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 integrity0.0010.000
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 head0.017
GPT teacher head0.221
Teacher spread0.204 · 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.

Study designSimulation or modeling
Domainnot available
GenreOther

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
Published2017
Admission routes1
Has abstractyes

Explore more

Same topicIntegrated Energy Systems OptimizationFrench-language works237,207