{"title":"大规模动态经济调度中基于协同进化框架的协方差矩阵自适应进化策略","authors":"Qun Niu, Likun Wang, Ming-Sian You","doi":"10.1145/3426826.3426849","DOIUrl":null,"url":null,"abstract":"The increasing complexity of modern power systems has led to the emergence of large-scale dynamic economic dispatch (DED) problems. To solve a large-scale DED problem with high-dimensional decision variables and various constraints is still a challenge using most existing evolutionary algorithms. In this paper, we propose a covariance matrix adaptation evolution strategy based on cooperative co-evolutionary framework (CC-CMA-ES) using delta grouping for solving large-scale DED problem. The experiment results suggest that the CC-CMA-ES is a fast and accurate approach for large-scale DED problems in terms of computation time, solution quality and convergence speed. Integrating CMA-ES into CC the framework can reduce the computation time by 97.5%, compared with basic CMA-ES, revealing the great potential of CC-CMA-ES for solving more difficult large-scale DED problems.","PeriodicalId":202857,"journal":{"name":"Proceedings of the 2020 3rd International Conference on Machine Learning and Machine Intelligence","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Covariance Matrix Adaptation Evolution Strategy Based on Cooperative Co-Evolutionary Framework Using Delta Grouping for Large-Scale Dynamic Economic Dispatch\",\"authors\":\"Qun Niu, Likun Wang, Ming-Sian You\",\"doi\":\"10.1145/3426826.3426849\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The increasing complexity of modern power systems has led to the emergence of large-scale dynamic economic dispatch (DED) problems. To solve a large-scale DED problem with high-dimensional decision variables and various constraints is still a challenge using most existing evolutionary algorithms. In this paper, we propose a covariance matrix adaptation evolution strategy based on cooperative co-evolutionary framework (CC-CMA-ES) using delta grouping for solving large-scale DED problem. The experiment results suggest that the CC-CMA-ES is a fast and accurate approach for large-scale DED problems in terms of computation time, solution quality and convergence speed. Integrating CMA-ES into CC the framework can reduce the computation time by 97.5%, compared with basic CMA-ES, revealing the great potential of CC-CMA-ES for solving more difficult large-scale DED problems.\",\"PeriodicalId\":202857,\"journal\":{\"name\":\"Proceedings of the 2020 3rd International Conference on Machine Learning and Machine Intelligence\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2020 3rd International Conference on Machine Learning and Machine Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3426826.3426849\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2020 3rd International Conference on Machine Learning and Machine Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3426826.3426849","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Covariance Matrix Adaptation Evolution Strategy Based on Cooperative Co-Evolutionary Framework Using Delta Grouping for Large-Scale Dynamic Economic Dispatch
The increasing complexity of modern power systems has led to the emergence of large-scale dynamic economic dispatch (DED) problems. To solve a large-scale DED problem with high-dimensional decision variables and various constraints is still a challenge using most existing evolutionary algorithms. In this paper, we propose a covariance matrix adaptation evolution strategy based on cooperative co-evolutionary framework (CC-CMA-ES) using delta grouping for solving large-scale DED problem. The experiment results suggest that the CC-CMA-ES is a fast and accurate approach for large-scale DED problems in terms of computation time, solution quality and convergence speed. Integrating CMA-ES into CC the framework can reduce the computation time by 97.5%, compared with basic CMA-ES, revealing the great potential of CC-CMA-ES for solving more difficult large-scale DED problems.