{"title":"风电并网系统能源市场远期结算","authors":"Akanksha Sharma, S. Jain","doi":"10.1109/ICCPEIC45300.2019.9082375","DOIUrl":null,"url":null,"abstract":"In this paper the forward market clearing of wind integrated power system considering the randomness in wind power generation is presented. The intermittent nature of wind power is characterized by Weibull probability density function (PDF). The aim is to minimize the cost of energy supplied by thermal and wind generators. The cost of energy also incorporates overestimation and underestimation cost of available wind power. Gravitational search algorithm (GSA) based scheduling is utilized for the market clearing purpose. The results have been obtained on IEEE 30-bus and IEEE 57-bus test systems to investigate the effectiveness of the presented algorithm for optimal scheduling.","PeriodicalId":120930,"journal":{"name":"2019 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Forward Clearing of Energy Market for Wind Incorporated Power System\",\"authors\":\"Akanksha Sharma, S. Jain\",\"doi\":\"10.1109/ICCPEIC45300.2019.9082375\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper the forward market clearing of wind integrated power system considering the randomness in wind power generation is presented. The intermittent nature of wind power is characterized by Weibull probability density function (PDF). The aim is to minimize the cost of energy supplied by thermal and wind generators. The cost of energy also incorporates overestimation and underestimation cost of available wind power. Gravitational search algorithm (GSA) based scheduling is utilized for the market clearing purpose. The results have been obtained on IEEE 30-bus and IEEE 57-bus test systems to investigate the effectiveness of the presented algorithm for optimal scheduling.\",\"PeriodicalId\":120930,\"journal\":{\"name\":\"2019 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCPEIC45300.2019.9082375\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCPEIC45300.2019.9082375","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Forward Clearing of Energy Market for Wind Incorporated Power System
In this paper the forward market clearing of wind integrated power system considering the randomness in wind power generation is presented. The intermittent nature of wind power is characterized by Weibull probability density function (PDF). The aim is to minimize the cost of energy supplied by thermal and wind generators. The cost of energy also incorporates overestimation and underestimation cost of available wind power. Gravitational search algorithm (GSA) based scheduling is utilized for the market clearing purpose. The results have been obtained on IEEE 30-bus and IEEE 57-bus test systems to investigate the effectiveness of the presented algorithm for optimal scheduling.
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