{"title":"考虑综合需求响应的改进WSO算法的低碳经济调度","authors":"Jiaqi Li","doi":"10.1002/cpe.70139","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>Aiming at the low carbon economic dispatch problem of the regional integrated energy system, a low carbon economic dispatch model combining integrated demand response and carbon capture and storage technology is proposed, and an improved great white shark optimization algorithm is used for solving. Experimental results show that this method can significantly reduce the system dispatch cost. Compared with traditional methods, the total dispatch cost is reduced by 22.81% and 17.77%, respectively. Meanwhile, the utilization rates of wind energy and solar energy are improved, and the curtailment rates of wind power and solar power are reduced to 0% respectively. In addition, the improved great white shark optimization algorithm exhibits a faster convergence speed and higher solution accuracy during the solving process. Its solution time cost is reduced by 66.45% and 45.74% compared with the traditional great white shark optimization algorithm and the whale optimization algorithm respectively. This research provides a new strategy for achieving the low-carbon economic operation of the regional integrated energy system and makes an important contribution to promoting the transformation of the energy structure and sustainable development.</p>\n </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 15-17","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"RIES Low-Carbon Economic Dispatch With Improved WSO Algorithm Considering Integrated Demand Response\",\"authors\":\"Jiaqi Li\",\"doi\":\"10.1002/cpe.70139\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>Aiming at the low carbon economic dispatch problem of the regional integrated energy system, a low carbon economic dispatch model combining integrated demand response and carbon capture and storage technology is proposed, and an improved great white shark optimization algorithm is used for solving. Experimental results show that this method can significantly reduce the system dispatch cost. Compared with traditional methods, the total dispatch cost is reduced by 22.81% and 17.77%, respectively. Meanwhile, the utilization rates of wind energy and solar energy are improved, and the curtailment rates of wind power and solar power are reduced to 0% respectively. In addition, the improved great white shark optimization algorithm exhibits a faster convergence speed and higher solution accuracy during the solving process. Its solution time cost is reduced by 66.45% and 45.74% compared with the traditional great white shark optimization algorithm and the whale optimization algorithm respectively. This research provides a new strategy for achieving the low-carbon economic operation of the regional integrated energy system and makes an important contribution to promoting the transformation of the energy structure and sustainable development.</p>\\n </div>\",\"PeriodicalId\":55214,\"journal\":{\"name\":\"Concurrency and Computation-Practice & Experience\",\"volume\":\"37 15-17\",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2025-05-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Concurrency and Computation-Practice & Experience\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/cpe.70139\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Concurrency and Computation-Practice & Experience","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cpe.70139","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
Aiming at the low carbon economic dispatch problem of the regional integrated energy system, a low carbon economic dispatch model combining integrated demand response and carbon capture and storage technology is proposed, and an improved great white shark optimization algorithm is used for solving. Experimental results show that this method can significantly reduce the system dispatch cost. Compared with traditional methods, the total dispatch cost is reduced by 22.81% and 17.77%, respectively. Meanwhile, the utilization rates of wind energy and solar energy are improved, and the curtailment rates of wind power and solar power are reduced to 0% respectively. In addition, the improved great white shark optimization algorithm exhibits a faster convergence speed and higher solution accuracy during the solving process. Its solution time cost is reduced by 66.45% and 45.74% compared with the traditional great white shark optimization algorithm and the whale optimization algorithm respectively. This research provides a new strategy for achieving the low-carbon economic operation of the regional integrated energy system and makes an important contribution to promoting the transformation of the energy structure and sustainable development.
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