{"title":"A new improved algorithm for optimal sizing of battery-supercapacitor based hybrid energy storage systems","authors":"S. Mandal, K. Mandal, M. De, G. Das","doi":"10.1109/EDCT.2018.8405059","DOIUrl":null,"url":null,"abstract":"One of the major challenges in harvesting energy from renewable energy sources is the intermittent nature of available energy sources like solar, wind etc. Thus, it is has become essential to deploy suitable energy storage devices to compensate for the intermittent and random output power generation from various resources. A hybrid energy storage systems (HESS) consisting of battery and supercapacitor is suitable to overcome the difficulties in battery storage system which is normally used. Differential evolution (DE) is one of the powerful evolutionary optimization and has been successfully applied to solve various optimization problems. But one of major difficulties in DE is the selection of control parameters. A wrong parameter selection may lead to premature convergence and even stagnation. In the this work, a new improved algorithm using differential evolution and chaos theory is proposed for optimal sizing of hybrid energy storage system consisting of battery and super capacitor with an aim to avoid premature convergence. A hybrid system consisting of solar and wind is considered for the present work. A suitable objective function is developed which is optimized under several equality and inequality constraints. Simulation results are presented. A comparison of the results with other heuristic techniques is also presented and it shows that proposed techniques can produce good quality solutions.","PeriodicalId":6507,"journal":{"name":"2018 Emerging Trends in Electronic Devices and Computational Techniques (EDCT)","volume":"66 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2018-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Emerging Trends in Electronic Devices and Computational Techniques (EDCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EDCT.2018.8405059","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
One of the major challenges in harvesting energy from renewable energy sources is the intermittent nature of available energy sources like solar, wind etc. Thus, it is has become essential to deploy suitable energy storage devices to compensate for the intermittent and random output power generation from various resources. A hybrid energy storage systems (HESS) consisting of battery and supercapacitor is suitable to overcome the difficulties in battery storage system which is normally used. Differential evolution (DE) is one of the powerful evolutionary optimization and has been successfully applied to solve various optimization problems. But one of major difficulties in DE is the selection of control parameters. A wrong parameter selection may lead to premature convergence and even stagnation. In the this work, a new improved algorithm using differential evolution and chaos theory is proposed for optimal sizing of hybrid energy storage system consisting of battery and super capacitor with an aim to avoid premature convergence. A hybrid system consisting of solar and wind is considered for the present work. A suitable objective function is developed which is optimized under several equality and inequality constraints. Simulation results are presented. A comparison of the results with other heuristic techniques is also presented and it shows that proposed techniques can produce good quality solutions.