L. Gomes, F. Fernandes, P. Faria, M. Silva, Z. Vale, C. Ramos
{"title":"实时模拟满足风电变化的实时定价需求响应","authors":"L. Gomes, F. Fernandes, P. Faria, M. Silva, Z. Vale, C. Ramos","doi":"10.1109/ISGTEUROPE.2014.7028777","DOIUrl":null,"url":null,"abstract":"Recent changes of paradigm in power systems opened the opportunity to the active participation of new players. The small and medium players gain new opportunities while participating in demand response programs. This paper explores the optimal resources scheduling in two distinct levels. First, the network operator facing large wind power variations makes use of real time pricing to induce consumers to meet wind power variations. Then, at the consumer level, each load is managed according to the consumer preferences. The two-level resources schedule has been implemented in a real-time simulation platform, which uses hardware for consumer' loads control. The illustrative example includes a situation of large lack of wind power and focuses on a consumer with 18 loads.","PeriodicalId":299515,"journal":{"name":"IEEE PES Innovative Smart Grid Technologies, Europe","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Real-time simulation of real-time pricing demand response to meet wind variations\",\"authors\":\"L. Gomes, F. Fernandes, P. Faria, M. Silva, Z. Vale, C. Ramos\",\"doi\":\"10.1109/ISGTEUROPE.2014.7028777\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recent changes of paradigm in power systems opened the opportunity to the active participation of new players. The small and medium players gain new opportunities while participating in demand response programs. This paper explores the optimal resources scheduling in two distinct levels. First, the network operator facing large wind power variations makes use of real time pricing to induce consumers to meet wind power variations. Then, at the consumer level, each load is managed according to the consumer preferences. The two-level resources schedule has been implemented in a real-time simulation platform, which uses hardware for consumer' loads control. The illustrative example includes a situation of large lack of wind power and focuses on a consumer with 18 loads.\",\"PeriodicalId\":299515,\"journal\":{\"name\":\"IEEE PES Innovative Smart Grid Technologies, Europe\",\"volume\":\"75 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-10-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE PES Innovative Smart Grid Technologies, Europe\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISGTEUROPE.2014.7028777\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE PES Innovative Smart Grid Technologies, Europe","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISGTEUROPE.2014.7028777","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Real-time simulation of real-time pricing demand response to meet wind variations
Recent changes of paradigm in power systems opened the opportunity to the active participation of new players. The small and medium players gain new opportunities while participating in demand response programs. This paper explores the optimal resources scheduling in two distinct levels. First, the network operator facing large wind power variations makes use of real time pricing to induce consumers to meet wind power variations. Then, at the consumer level, each load is managed according to the consumer preferences. The two-level resources schedule has been implemented in a real-time simulation platform, which uses hardware for consumer' loads control. The illustrative example includes a situation of large lack of wind power and focuses on a consumer with 18 loads.