{"title":"温度和需求相关条件下的鲁棒机组承诺模型","authors":"Anna Danandeh, Wen Wang, Bo Zeng, B. Buckley","doi":"10.1109/NAPS.2016.7747863","DOIUrl":null,"url":null,"abstract":"Robust Unit Commitment (UC) model has been intensively investigated as an effective approach to hedge against randomness and risks. All existing robust UC formulations consider uncertainties in demand and/or cost. We observe that, nevertheless, a power system could be seriously affected by surrounding temperature and there is a strong relationship among the efficiency of gas generators, demand and temperature. With that observation, we develop a robust optimization model considering correlated uncertainties in temperature and demand forecasting, and the impact of the former one on generating efficiency. Numerical experiments are conducted on a typical IEEE test system to analyse our formulation and the impact of uncertain temperature.","PeriodicalId":249041,"journal":{"name":"2016 North American Power Symposium (NAPS)","volume":"240 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A robust unit commitment model under correlated temperatures and demands\",\"authors\":\"Anna Danandeh, Wen Wang, Bo Zeng, B. Buckley\",\"doi\":\"10.1109/NAPS.2016.7747863\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Robust Unit Commitment (UC) model has been intensively investigated as an effective approach to hedge against randomness and risks. All existing robust UC formulations consider uncertainties in demand and/or cost. We observe that, nevertheless, a power system could be seriously affected by surrounding temperature and there is a strong relationship among the efficiency of gas generators, demand and temperature. With that observation, we develop a robust optimization model considering correlated uncertainties in temperature and demand forecasting, and the impact of the former one on generating efficiency. Numerical experiments are conducted on a typical IEEE test system to analyse our formulation and the impact of uncertain temperature.\",\"PeriodicalId\":249041,\"journal\":{\"name\":\"2016 North American Power Symposium (NAPS)\",\"volume\":\"240 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 North American Power Symposium (NAPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAPS.2016.7747863\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 North American Power Symposium (NAPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAPS.2016.7747863","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A robust unit commitment model under correlated temperatures and demands
Robust Unit Commitment (UC) model has been intensively investigated as an effective approach to hedge against randomness and risks. All existing robust UC formulations consider uncertainties in demand and/or cost. We observe that, nevertheless, a power system could be seriously affected by surrounding temperature and there is a strong relationship among the efficiency of gas generators, demand and temperature. With that observation, we develop a robust optimization model considering correlated uncertainties in temperature and demand forecasting, and the impact of the former one on generating efficiency. Numerical experiments are conducted on a typical IEEE test system to analyse our formulation and the impact of uncertain temperature.