Vojtech Blazek, L. Prokop, S. Mišák, Pavel Kedroň, Ivo Pergl
{"title":"Impact of Energy Consumption Optimisation on the Electrical Self-Sufficiency of a Microgrid with Vehicle-to-Grid Technology","authors":"Vojtech Blazek, L. Prokop, S. Mišák, Pavel Kedroň, Ivo Pergl","doi":"10.1109/ECTIDAMTNCON57770.2023.10139540","DOIUrl":null,"url":null,"abstract":"This article presents optimisation tools for optimising electric consumption in household microgrid environments with Vehicle To Grid (V2G) technology. Optimalisation tools are based on a Non-dominated sorting genetic algorithm II (NSGA-2). Furthermore, this article describes the digitalised digital twin of the physical microgrid. The physical microgrid simulates a typical Czech household whose primary stochastic energy source is a photovoltaic plant (PV). Microgrid works off-grid. The study's results showed a positive impact on optimising potential electrical self-sufficiency in the microgrid in the conditions of Central Europe. The optimization results most efficiently under tariff mode with electric vehicles (EV). The worst results are achieved in the microgrid, where optimisation is disabled, but tariff mode is activated. This article has served as an initial study of whether it Is worthwhile to use this optimisation.","PeriodicalId":38808,"journal":{"name":"Transactions on Electrical Engineering, Electronics, and Communications","volume":"30 1","pages":"279-283"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transactions on Electrical Engineering, Electronics, and Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECTIDAMTNCON57770.2023.10139540","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0
Abstract
This article presents optimisation tools for optimising electric consumption in household microgrid environments with Vehicle To Grid (V2G) technology. Optimalisation tools are based on a Non-dominated sorting genetic algorithm II (NSGA-2). Furthermore, this article describes the digitalised digital twin of the physical microgrid. The physical microgrid simulates a typical Czech household whose primary stochastic energy source is a photovoltaic plant (PV). Microgrid works off-grid. The study's results showed a positive impact on optimising potential electrical self-sufficiency in the microgrid in the conditions of Central Europe. The optimization results most efficiently under tariff mode with electric vehicles (EV). The worst results are achieved in the microgrid, where optimisation is disabled, but tariff mode is activated. This article has served as an initial study of whether it Is worthwhile to use this optimisation.