{"title":"求解混合动力经济排放调度的进化优化算法约束处理方法","authors":"Yubin Yao, Tianfeng Ren","doi":"10.1109/AEES56284.2022.10079493","DOIUrl":null,"url":null,"abstract":"With the rapid development of renewable energy, hybrid dynamic economic emission dispatch (HDEED) which considering renewable energy has gradually become a heated topic. HDEED is a non-convex, strongly constrained, high-dimensional multi-objective optimization problem, which usually solved by evolutionary optimization algorithm. In order to meet the constraints in HDEED, this paper proposes a new constraints handling method. The proposed method distributes the imbalance power among power generators in a weighted or prioritized way under the premise of preferential consumption of renewable energy and satisfying inequality constraints. The method not only meets all constraints in HDEED problem, but also improves convergence of the algorithm and the diversity of the Pareto solution set. A case involving thermal power units, wind farms and photovoltaic plant is used to test the performance of the proposed method which combined with a classical multi-objective evolutionary optimization algorithm NSGA-II. The result shows that the proposed method is effective and superior to the compared methods.","PeriodicalId":227496,"journal":{"name":"2022 3rd International Conference on Advanced Electrical and Energy Systems (AEES)","volume":"11 3","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Constraints Handling Method for Evolutionary Optimization Algorithm in Solving Hybrid Dynamic Economic Emission Dispatch\",\"authors\":\"Yubin Yao, Tianfeng Ren\",\"doi\":\"10.1109/AEES56284.2022.10079493\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the rapid development of renewable energy, hybrid dynamic economic emission dispatch (HDEED) which considering renewable energy has gradually become a heated topic. HDEED is a non-convex, strongly constrained, high-dimensional multi-objective optimization problem, which usually solved by evolutionary optimization algorithm. In order to meet the constraints in HDEED, this paper proposes a new constraints handling method. The proposed method distributes the imbalance power among power generators in a weighted or prioritized way under the premise of preferential consumption of renewable energy and satisfying inequality constraints. The method not only meets all constraints in HDEED problem, but also improves convergence of the algorithm and the diversity of the Pareto solution set. A case involving thermal power units, wind farms and photovoltaic plant is used to test the performance of the proposed method which combined with a classical multi-objective evolutionary optimization algorithm NSGA-II. The result shows that the proposed method is effective and superior to the compared methods.\",\"PeriodicalId\":227496,\"journal\":{\"name\":\"2022 3rd International Conference on Advanced Electrical and Energy Systems (AEES)\",\"volume\":\"11 3\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 3rd International Conference on Advanced Electrical and Energy Systems (AEES)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AEES56284.2022.10079493\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 3rd International Conference on Advanced Electrical and Energy Systems (AEES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AEES56284.2022.10079493","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Constraints Handling Method for Evolutionary Optimization Algorithm in Solving Hybrid Dynamic Economic Emission Dispatch
With the rapid development of renewable energy, hybrid dynamic economic emission dispatch (HDEED) which considering renewable energy has gradually become a heated topic. HDEED is a non-convex, strongly constrained, high-dimensional multi-objective optimization problem, which usually solved by evolutionary optimization algorithm. In order to meet the constraints in HDEED, this paper proposes a new constraints handling method. The proposed method distributes the imbalance power among power generators in a weighted or prioritized way under the premise of preferential consumption of renewable energy and satisfying inequality constraints. The method not only meets all constraints in HDEED problem, but also improves convergence of the algorithm and the diversity of the Pareto solution set. A case involving thermal power units, wind farms and photovoltaic plant is used to test the performance of the proposed method which combined with a classical multi-objective evolutionary optimization algorithm NSGA-II. The result shows that the proposed method is effective and superior to the compared methods.