{"title":"Optimal microgrid sizing and daily capacity stored analysis in summer and winter season","authors":"M. Kharrich, Y. Sayouti, M. Akherraz","doi":"10.1109/ICOA.2018.8370521","DOIUrl":null,"url":null,"abstract":"This paper presents an optimal sizing for hybrid microgrid based on photovoltaic, wind, diesel and battery energy storage system. Evolutionary algorithms (EA) are used in order to optimize the Net Present Cost (NPC) respecting reliability constraints like the Loss of Power Supply Probability (LPSP), Availability and Renewable Fraction (RF). Particle swarm optimization (PSO) and invasive weeds optimization (IWO) algorithms are compared in this paper. Battery storage is considered in summer and winter to determine their daily storage. The results of this study show that PSO converges to the best solution with NPC 59899.91$ and LCOE of 0.384 $/kWh, Furthermore, the battery is most used and most efficacy in summer than the winter.","PeriodicalId":433166,"journal":{"name":"2018 4th International Conference on Optimization and Applications (ICOA)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 4th International Conference on Optimization and Applications (ICOA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOA.2018.8370521","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
This paper presents an optimal sizing for hybrid microgrid based on photovoltaic, wind, diesel and battery energy storage system. Evolutionary algorithms (EA) are used in order to optimize the Net Present Cost (NPC) respecting reliability constraints like the Loss of Power Supply Probability (LPSP), Availability and Renewable Fraction (RF). Particle swarm optimization (PSO) and invasive weeds optimization (IWO) algorithms are compared in this paper. Battery storage is considered in summer and winter to determine their daily storage. The results of this study show that PSO converges to the best solution with NPC 59899.91$ and LCOE of 0.384 $/kWh, Furthermore, the battery is most used and most efficacy in summer than the winter.