{"title":"优化风电和热电机组的经济/环境调度","authors":"A. Al-Awami, E. Sortomme, M. El-Sharkawi","doi":"10.1109/PES.2009.5275667","DOIUrl":null,"url":null,"abstract":"In this paper, the economic/environmental dispatch for a smart grid with wind and thermal units is formulated. The formulation takes into account the stochastic nature of wind power output and the imbalance charges due to the mismatch between the actual and scheduled wind power outputs. Because minimizing the operating cost of thermal and wind units, and minimizing the emissions of thermal units are two conflicting objectives, multi-objective optimization (MOO) technique is used. With MOO, a set of solutions that are optimal in the Pareto sense is identified. An enhanced multi-objective particle swarm optimization (MO-PSO) is proposed to search for the set of Pareto-optimal solutions. The effect of different system conditions on the Pareto-optimal solutions is investigated. These system conditions include load level and different imbalance cost coefficients. Test results show the effectiveness of the proposed technique in identifying the set of Pareto optimal solutions. This technique is an important tool that system operators require in order to operate the grid with high penetration of wind power more efficiently while maintaining emissions within restricted limits.","PeriodicalId":258632,"journal":{"name":"2009 IEEE Power & Energy Society General Meeting","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"40","resultStr":"{\"title\":\"Optimizing economic/environmental dispatch with wind and thermal units\",\"authors\":\"A. Al-Awami, E. Sortomme, M. El-Sharkawi\",\"doi\":\"10.1109/PES.2009.5275667\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, the economic/environmental dispatch for a smart grid with wind and thermal units is formulated. The formulation takes into account the stochastic nature of wind power output and the imbalance charges due to the mismatch between the actual and scheduled wind power outputs. Because minimizing the operating cost of thermal and wind units, and minimizing the emissions of thermal units are two conflicting objectives, multi-objective optimization (MOO) technique is used. With MOO, a set of solutions that are optimal in the Pareto sense is identified. An enhanced multi-objective particle swarm optimization (MO-PSO) is proposed to search for the set of Pareto-optimal solutions. The effect of different system conditions on the Pareto-optimal solutions is investigated. These system conditions include load level and different imbalance cost coefficients. Test results show the effectiveness of the proposed technique in identifying the set of Pareto optimal solutions. This technique is an important tool that system operators require in order to operate the grid with high penetration of wind power more efficiently while maintaining emissions within restricted limits.\",\"PeriodicalId\":258632,\"journal\":{\"name\":\"2009 IEEE Power & Energy Society General Meeting\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"40\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE Power & Energy Society General Meeting\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PES.2009.5275667\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE Power & Energy Society General Meeting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PES.2009.5275667","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimizing economic/environmental dispatch with wind and thermal units
In this paper, the economic/environmental dispatch for a smart grid with wind and thermal units is formulated. The formulation takes into account the stochastic nature of wind power output and the imbalance charges due to the mismatch between the actual and scheduled wind power outputs. Because minimizing the operating cost of thermal and wind units, and minimizing the emissions of thermal units are two conflicting objectives, multi-objective optimization (MOO) technique is used. With MOO, a set of solutions that are optimal in the Pareto sense is identified. An enhanced multi-objective particle swarm optimization (MO-PSO) is proposed to search for the set of Pareto-optimal solutions. The effect of different system conditions on the Pareto-optimal solutions is investigated. These system conditions include load level and different imbalance cost coefficients. Test results show the effectiveness of the proposed technique in identifying the set of Pareto optimal solutions. This technique is an important tool that system operators require in order to operate the grid with high penetration of wind power more efficiently while maintaining emissions within restricted limits.