{"title":"基于混合储能系统的风电全寿命成本优化控制","authors":"Dongsheng Li, Fenglong Lu, Q. Lv, Li Shang","doi":"10.1109/NAPS.2013.6666901","DOIUrl":null,"url":null,"abstract":"This paper presents the use of hybrid energy storage, composed of ultracapacitor and Lithiumion battery, to improve wind power stability. A control algorithm based on artificial neural network is proposed to manage the run-time use of the hybrid energy storage system to (1) optimize wind power predictability hence power grid stability, and (2) minimize the overall lifetime cost of the energy storage system. Evaluations using wind farm data demonstrate that, compared with two recently proposed control methods, the proposed control algorithm can extend system lifetime by 62% and 143%, and reduce the overall lifetime energy storage system cost (20 years) by 41% and 59%, respectively.","PeriodicalId":421943,"journal":{"name":"2013 North American Power Symposium (NAPS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Lifetime cost optimized wind power control using hybrid energy storage system\",\"authors\":\"Dongsheng Li, Fenglong Lu, Q. Lv, Li Shang\",\"doi\":\"10.1109/NAPS.2013.6666901\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents the use of hybrid energy storage, composed of ultracapacitor and Lithiumion battery, to improve wind power stability. A control algorithm based on artificial neural network is proposed to manage the run-time use of the hybrid energy storage system to (1) optimize wind power predictability hence power grid stability, and (2) minimize the overall lifetime cost of the energy storage system. Evaluations using wind farm data demonstrate that, compared with two recently proposed control methods, the proposed control algorithm can extend system lifetime by 62% and 143%, and reduce the overall lifetime energy storage system cost (20 years) by 41% and 59%, respectively.\",\"PeriodicalId\":421943,\"journal\":{\"name\":\"2013 North American Power Symposium (NAPS)\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 North American Power Symposium (NAPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAPS.2013.6666901\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 North American Power Symposium (NAPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAPS.2013.6666901","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Lifetime cost optimized wind power control using hybrid energy storage system
This paper presents the use of hybrid energy storage, composed of ultracapacitor and Lithiumion battery, to improve wind power stability. A control algorithm based on artificial neural network is proposed to manage the run-time use of the hybrid energy storage system to (1) optimize wind power predictability hence power grid stability, and (2) minimize the overall lifetime cost of the energy storage system. Evaluations using wind farm data demonstrate that, compared with two recently proposed control methods, the proposed control algorithm can extend system lifetime by 62% and 143%, and reduce the overall lifetime energy storage system cost (20 years) by 41% and 59%, respectively.
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