AN EVOLUTIONARY ALGORITHM-BASED MODEL PREDICTIVE CONTROL FOR COMBINED ELECTRICAL AND THERMAL ENERGY SYSTEMS

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Energy storage is crucial to increase renewable energy adoption in construction. By optimizing their control strategies, operational costs decrease and return on investment improves. Model Predictive Controls (MPC) have been used to optimize the use of energy storage but are costly to implement. This paper presents an MPC with a generalized mathematical model for electrical and thermal storage. A methodology is introduced to account for physical restrictions. Three evolutionary algorithms were compared for the optimization and a Genetic Algorithm was found to best reduce the energy bill with average daily savings of 38.7 %.

Original languageEnglish
Title of host publicationProceedings of the 2024 European Conference on Computing in Construction
EditorsMarijana Srećković, Mohamad Kassem, Ranjith Soman, Athanasios Chassiakos
PublisherEuropean Council on Computing in Construction (EC3)
Pages703-710
Number of pages8
ISBN (Print)9789083451305
DOIs
Publication statusPublished - 2024
EventEuropean Conference on Computing in Construction, EC3 2024 - Chania, Greece
Duration: 14 Jul 202417 Jul 2024

Publication series

NameProceedings of the European Conference on Computing in Construction
Volume2024
ISSN (Electronic)2684-1150

Conference

ConferenceEuropean Conference on Computing in Construction, EC3 2024
Country/TerritoryGreece
CityChania
Period14/07/2417/07/24

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