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Modeling and Scheduling of an Integrated Thermal and Electrical Building Microgrid

2020· article· en· W3116338864 on OpenAlexafffund
Alireza Lorestani, Jorge Chebeir, Mehdi Narimani, James S. Cotton

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsThermal energy storageHeat exchangerAutomotive engineeringThermal massThermalMicrogridElectric powerElectricityProcess engineeringEnvironmental scienceMechanical engineeringEngineeringNuclear engineeringElectrical engineeringPower (physics)Renewable energy

Abstract

fetched live from OpenAlex

This study proposes a day-ahead operation scheduling of a building microgrid (BMG) with electrical and thermal loads, on-site generation units and storage systems. To do so, all the components including heat exchangers, water pumps, battery, combined heat and power (CHP) unit, stratified hot water tank, backup boiler, and heat pump (HP) are modeled in detail. The electrical and thermal sections of the BMG are integrated through the coupled use of the CHP unit, HP, and water pumps. This integration provides the capability of manipulating thermal variables such as temperatures and mass flow rates in such manner that the total electricity demand follows the desired profile and both electrical and thermal loads of customers are fully met. Results show the competence of the developed control strategy for practical applications. The potential of levelizing loads through the integration of thermal and electrical sections of a BMG by taking the advantages of CHP, HP, and hot water tank, is demonstrated.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.294
Threshold uncertainty score0.264

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 head0.007
GPT teacher head0.190
Teacher spread0.183 · 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

Citations2
Published2020
Admission routes2
Has abstractyes

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