{"title":"可再生能源发电量和负荷分布不均的区域电力系统统一多目标优化","authors":"Long Zhao, Xiangfei Meng, Lichao Yang, Jia Wei","doi":"10.1002/eng2.12768","DOIUrl":null,"url":null,"abstract":"<p>The optimization for large-scale power systems with unequal renewable energy distribution is an important and urgent task to collaborate operations of the participated sub-grids. This article proposes a novel method by utilizing the unified multi-objective optimization (MOO) to integrate diverse strategies to a comprehensive problem. For this aim, individual optimal model is first established to describe the demands of each sub-grid. The overall objectives are unified in terms of economy costs. This unification integrates evaluate different optimized results without loss of generality. The global objective is the weighted sum of the individual objectives with empirical coefficient. Thus, the internal coupled restrictions and influences among sub-grids can be solved simultaneously. Finally, by adjusting the corresponding weights according to the preferred requirement, the optimized solution can effectively allocate renewable energy throughout all sub-grids. Consequently, both individual and global requirements can be met at utmost. The proposed unified MOO is tested on the configured systems based on multiple modified PJM 9-bus grids. Satisfying the global optimum of the multi-region joint system, the total system cost increases by 15.1%, the industrial zone cost increases by 21.4%, and the residential load shedding loss cost increases by 27.3%. Although each region has to sacrifice some of its benefits, the compromise operational behavior ensures that the total cost is optimal. Numerical results verify the effectiveness in achieving the promising global optimal solution, and the flexibility in meeting the requirements of different sub-grids.</p>","PeriodicalId":72922,"journal":{"name":"Engineering reports : open access","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/eng2.12768","citationCount":"1","resultStr":"{\"title\":\"Unified multi-objective optimization for regional power systems with unequal distribution of renewable energy generation and load\",\"authors\":\"Long Zhao, Xiangfei Meng, Lichao Yang, Jia Wei\",\"doi\":\"10.1002/eng2.12768\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The optimization for large-scale power systems with unequal renewable energy distribution is an important and urgent task to collaborate operations of the participated sub-grids. This article proposes a novel method by utilizing the unified multi-objective optimization (MOO) to integrate diverse strategies to a comprehensive problem. For this aim, individual optimal model is first established to describe the demands of each sub-grid. The overall objectives are unified in terms of economy costs. This unification integrates evaluate different optimized results without loss of generality. The global objective is the weighted sum of the individual objectives with empirical coefficient. Thus, the internal coupled restrictions and influences among sub-grids can be solved simultaneously. Finally, by adjusting the corresponding weights according to the preferred requirement, the optimized solution can effectively allocate renewable energy throughout all sub-grids. Consequently, both individual and global requirements can be met at utmost. The proposed unified MOO is tested on the configured systems based on multiple modified PJM 9-bus grids. Satisfying the global optimum of the multi-region joint system, the total system cost increases by 15.1%, the industrial zone cost increases by 21.4%, and the residential load shedding loss cost increases by 27.3%. Although each region has to sacrifice some of its benefits, the compromise operational behavior ensures that the total cost is optimal. Numerical results verify the effectiveness in achieving the promising global optimal solution, and the flexibility in meeting the requirements of different sub-grids.</p>\",\"PeriodicalId\":72922,\"journal\":{\"name\":\"Engineering reports : open access\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2023-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/eng2.12768\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Engineering reports : open access\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/eng2.12768\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering reports : open access","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/eng2.12768","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Unified multi-objective optimization for regional power systems with unequal distribution of renewable energy generation and load
The optimization for large-scale power systems with unequal renewable energy distribution is an important and urgent task to collaborate operations of the participated sub-grids. This article proposes a novel method by utilizing the unified multi-objective optimization (MOO) to integrate diverse strategies to a comprehensive problem. For this aim, individual optimal model is first established to describe the demands of each sub-grid. The overall objectives are unified in terms of economy costs. This unification integrates evaluate different optimized results without loss of generality. The global objective is the weighted sum of the individual objectives with empirical coefficient. Thus, the internal coupled restrictions and influences among sub-grids can be solved simultaneously. Finally, by adjusting the corresponding weights according to the preferred requirement, the optimized solution can effectively allocate renewable energy throughout all sub-grids. Consequently, both individual and global requirements can be met at utmost. The proposed unified MOO is tested on the configured systems based on multiple modified PJM 9-bus grids. Satisfying the global optimum of the multi-region joint system, the total system cost increases by 15.1%, the industrial zone cost increases by 21.4%, and the residential load shedding loss cost increases by 27.3%. Although each region has to sacrifice some of its benefits, the compromise operational behavior ensures that the total cost is optimal. Numerical results verify the effectiveness in achieving the promising global optimal solution, and the flexibility in meeting the requirements of different sub-grids.