Optimization framework for coordinated operation of home energy management system and Volt-VAR optimization in unbalanced active distribution networks considering uncertainties
DC Field | Value | Language |
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dc.contributor.author | Mak, D. | - |
dc.contributor.author | Choi, D.-H. | - |
dc.date.accessioned | 2022-01-12T05:40:47Z | - |
dc.date.available | 2022-01-12T05:40:47Z | - |
dc.date.issued | 2020-10 | - |
dc.identifier.issn | 0306-2619 | - |
dc.identifier.issn | 1872-9118 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/53343 | - |
dc.description.abstract | This study proposes an optimization framework that coordinates the operations of a home energy management system (HEMS) in a low-voltage (LV) distribution network and Volt/VAR optimization (VVO) in a medium-voltage (MV) distribution network through flexible electricity consumption and production of prosumers. The proposed framework consists of a three-level optimization problem, which corresponds to the HEMS for a prosumer at the first level, HEMS aggregator at the second level, and VVO at the third level. The optimal operations of home appliances and distributed energy resources are scheduled in the HEMS according to the prosumer's preferred appliance scheduling and comfort level. Given the optimal energy consumption schedules from multiple HEMSs, the HEMS aggregator recalculates them while interacting with the VVO, which monitors and controls the MV distribution network efficiently. Furthermore, to incorporate the uncertainty for the predicted errors of residential solar photovoltaic generation and outdoor temperature into the proposed framework, the deterministic optimization (DO)-based HEMS aggregator model is reformulated into a chance constrained optimization (CCO)-based model. Numerical examples tested in IEEE 13-node MV and CIGRE 18-node LV distribution systems show that, in contrast with a method without coordination of HEMS and VVO, the proposed DO-based approach reduces the total energy losses, active energy consumption, and reactive energy consumption by 21.03%,7.62%, and 115.51%, respectively, in the LV system, and 2.34%,1.36%, and 4.07%, respectively, in the MV system. In addition, the performance of the proposed CCO-based approach was validated in terms of probability level of chance constraints. © 2020 Elsevier Ltd | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Elsevier Ltd | - |
dc.title | Optimization framework for coordinated operation of home energy management system and Volt-VAR optimization in unbalanced active distribution networks considering uncertainties | - |
dc.type | Article | - |
dc.identifier.doi | 10.1016/j.apenergy.2020.115495 | - |
dc.identifier.bibliographicCitation | Applied Energy, v.276 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.wosid | 000571786500004 | - |
dc.identifier.scopusid | 2-s2.0-85088234984 | - |
dc.citation.title | Applied Energy | - |
dc.citation.volume | 276 | - |
dc.type.docType | Article | - |
dc.publisher.location | 영국 | - |
dc.subject.keywordAuthor | Active distribution network | - |
dc.subject.keywordAuthor | Demand response | - |
dc.subject.keywordAuthor | Home energy management system | - |
dc.subject.keywordAuthor | Prosumer | - |
dc.subject.keywordAuthor | Volt/VAR optimization | - |
dc.subject.keywordPlus | ELECTRIC VEHICLES | - |
dc.subject.keywordPlus | SMART | - |
dc.subject.keywordPlus | STORAGE | - |
dc.relation.journalResearchArea | Energy & Fuels | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Energy & Fuels | - |
dc.relation.journalWebOfScienceCategory | Engineering, Chemical | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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