Multi-objective framework for a home energy management system with the integration of solar energy and an electric vehicle using an augmented epsilon-constraint method and lexicographic optimization
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Huy, Truong Hoang Bao | - |
dc.contributor.author | Dinh, Huy Truong | - |
dc.contributor.author | Kim, Daehee | - |
dc.date.accessioned | 2023-03-09T04:40:25Z | - |
dc.date.available | 2023-03-09T04:40:25Z | - |
dc.date.issued | 2023-01 | - |
dc.identifier.issn | 2210-6707 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/22115 | - |
dc.description.abstract | Recent innovations in smart grid technology have increased the utilization of advanced techniques and control methods, enabling consumers to purchase and sell electricity more flexibly. Accordingly, the development of a home energy management system (HEMS) is urgently required to support residential consumers in consuming energy efficiently, achieving high satisfaction levels, and meeting grid specifications. Previous studies have only suggested simple HEMS models with one or two optimized objectives. Therefore, we propose a multi-objective mixed-integer linear programming paradigm for a comprehensive HEMS model which fully utilizes the vehicle-to-home and home-to-grid capabilities, while optimizing the energy cost, peak-to-average ratio (PAR), and discomfort index (DI). Also, an integration method of the augmented epsilon-constraint with lexicographic opti-mization is presented for effectively addressing any multi-objective HEMS problems. The proposed approach is validated across different simulations using both deterministic and stochastic models. The simulation results reveal that the energy costs and PAR can be reduced by 47.96% and 55.24%, respectively, whereas the DI is maintained at a minimum value. Extensive simulations related to the storage capacity, solar photovoltaic sizing, and uncertainty parameters are also analyzed. The proposed HEMS framework is confirmed to be a viable approach for optimally coordinating different home devices. | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Elsevier BV | - |
dc.title | Multi-objective framework for a home energy management system with the integration of solar energy and an electric vehicle using an augmented epsilon-constraint method and lexicographic optimization | - |
dc.type | Article | - |
dc.publisher.location | 네델란드 | - |
dc.identifier.doi | 10.1016/j.scs.2022.104289 | - |
dc.identifier.scopusid | 2-s2.0-85141536709 | - |
dc.identifier.wosid | 000913146900003 | - |
dc.identifier.bibliographicCitation | Sustainable Cities and Society, v.88 | - |
dc.citation.title | Sustainable Cities and Society | - |
dc.citation.volume | 88 | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Construction & Building Technology | - |
dc.relation.journalResearchArea | Science & Technology - Other Topics | - |
dc.relation.journalResearchArea | Energy & Fuels | - |
dc.relation.journalWebOfScienceCategory | Construction & Building Technology | - |
dc.relation.journalWebOfScienceCategory | Green & Sustainable Science & Technology | - |
dc.relation.journalWebOfScienceCategory | Energy & Fuels | - |
dc.subject.keywordPlus | SMART HOMES | - |
dc.subject.keywordPlus | STORAGE | - |
dc.subject.keywordPlus | ALGORITHMS | - |
dc.subject.keywordAuthor | Home energy management system (HEMS) | - |
dc.subject.keywordAuthor | Multi-objective optimization | - |
dc.subject.keywordAuthor | Augmented ?-constraint | - |
dc.subject.keywordAuthor | Lexicographic optimization | - |
dc.subject.keywordAuthor | Electric vehicle | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(31538) 22, Soonchunhyang-ro, Asan-si, Chungcheongnam-do, Republic of Korea+82-41-530-1114
COPYRIGHT 2021 by SOONCHUNHYANG UNIVERSITY ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.