C. Truong, Daniel May, Rodrigo Martins, P. Musílek, A. Jossen, H. Hesse
{"title":"Cuckoo-search optimized fuzzy-logic control of stationary battery storage systems","authors":"C. Truong, Daniel May, Rodrigo Martins, P. Musílek, A. Jossen, H. Hesse","doi":"10.1109/EPEC.2017.8286239","DOIUrl":null,"url":null,"abstract":"Energy storage systems are acknowledged as key components for transforming the power system towards low-carbon technology. The performance and resulting benefit of energy storage systems are determined by their operation strategies. We present a generic and adaptive control algorithm, based on fuzzy-logic and optimized by a meta heuristic search method. The performance of the algorithm is demonstrated in a solar home context, with the aim to alleviate the voltage rise in the low-voltage distribution grid caused by renewable energy generation. This is achieved by reducing the household's peak feed-in of each day. The obtained results show that the proposed algorithm performs similarly well as a rule-based reference algorithm, specifically designed to reduce the daily feed-in peak. At the same time, the generic structure of the proposed controller is by far more versatile, as it allows its application in a variety of scenarios just by modifying the objective function for the search algorithm.","PeriodicalId":141250,"journal":{"name":"2017 IEEE Electrical Power and Energy Conference (EPEC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Electrical Power and Energy Conference (EPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EPEC.2017.8286239","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Energy storage systems are acknowledged as key components for transforming the power system towards low-carbon technology. The performance and resulting benefit of energy storage systems are determined by their operation strategies. We present a generic and adaptive control algorithm, based on fuzzy-logic and optimized by a meta heuristic search method. The performance of the algorithm is demonstrated in a solar home context, with the aim to alleviate the voltage rise in the low-voltage distribution grid caused by renewable energy generation. This is achieved by reducing the household's peak feed-in of each day. The obtained results show that the proposed algorithm performs similarly well as a rule-based reference algorithm, specifically designed to reduce the daily feed-in peak. At the same time, the generic structure of the proposed controller is by far more versatile, as it allows its application in a variety of scenarios just by modifying the objective function for the search algorithm.