{"title":"基于优化粒子群算法的微电网智能调度研究","authors":"Zhen Nie, Rui Zhang","doi":"10.1002/adc2.157","DOIUrl":null,"url":null,"abstract":"<p>In the process of grid connection of irregular output micro-grid systems, it is of great research significance to make micro-grid scheduling operate more effectively and economically. To minimize the environmental and total operating costs of the micro-grid intelligent scheduling system during grid connection, this study proposes a micro-grid intelligent scheduling model based on an optimized particle swarm optimization algorithm. The optimized particle swarm algorithm mainly improves the problem of the particle swarm algorithm being prone to local optima, making it reduce the possibility of local convergence. Comparative tests were conducted on the improved IPSO algorithm, and the results showed that the non-dominated solution concentration pollution emissions obtained by the improved IPSO algorithm were at least 18326 Ib, which was lower than the comparison algorithm. In the empirical analysis of the intelligent scheduling model based on the improved IPSO algorithm, the convergence and satisfaction of the model were 0.0054 and 0.922, respectively, which were superior to the comparison algorithm. The above results indicate that the intelligent scheduling model for micro-grid based on the improved IPSO algorithm has good economy and stability. Compared with traditional energy dispatch methods, this energy dispatch mode has higher economic benefits and is of great significance for promoting the development of micro-grid.</p>","PeriodicalId":100030,"journal":{"name":"Advanced Control for Applications","volume":"6 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adc2.157","citationCount":"0","resultStr":"{\"title\":\"Research on intelligent dispatching of micro-grid according to optimized particle swarm algorithm\",\"authors\":\"Zhen Nie, Rui Zhang\",\"doi\":\"10.1002/adc2.157\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>In the process of grid connection of irregular output micro-grid systems, it is of great research significance to make micro-grid scheduling operate more effectively and economically. To minimize the environmental and total operating costs of the micro-grid intelligent scheduling system during grid connection, this study proposes a micro-grid intelligent scheduling model based on an optimized particle swarm optimization algorithm. The optimized particle swarm algorithm mainly improves the problem of the particle swarm algorithm being prone to local optima, making it reduce the possibility of local convergence. Comparative tests were conducted on the improved IPSO algorithm, and the results showed that the non-dominated solution concentration pollution emissions obtained by the improved IPSO algorithm were at least 18326 Ib, which was lower than the comparison algorithm. In the empirical analysis of the intelligent scheduling model based on the improved IPSO algorithm, the convergence and satisfaction of the model were 0.0054 and 0.922, respectively, which were superior to the comparison algorithm. The above results indicate that the intelligent scheduling model for micro-grid based on the improved IPSO algorithm has good economy and stability. Compared with traditional energy dispatch methods, this energy dispatch mode has higher economic benefits and is of great significance for promoting the development of micro-grid.</p>\",\"PeriodicalId\":100030,\"journal\":{\"name\":\"Advanced Control for Applications\",\"volume\":\"6 2\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adc2.157\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advanced Control for Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/adc2.157\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Control for Applications","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/adc2.157","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
在不规则输出微电网系统并网的过程中,如何使微电网调度更有效、更经济地运行具有重要的研究意义。为了最大限度地降低微电网智能调度系统在并网过程中的环境成本和总运行成本,本研究提出了一种基于优化粒子群优化算法的微电网智能调度模型。优化粒子群算法主要改善了粒子群算法容易出现局部最优的问题,使其降低了局部收敛的可能性。对改进后的 IPSO 算法进行了对比试验,结果表明,改进后的 IPSO 算法得到的非优势解浓度污染排放量至少为 18326 Ib,低于对比算法。在基于改进 IPSO 算法的智能调度模型的实证分析中,模型的收敛性和满意度分别为 0.0054 和 0.922,均优于对比算法。以上结果表明,基于改进 IPSO 算法的微电网智能调度模型具有良好的经济性和稳定性。与传统的能量调度方式相比,该能量调度模式具有更高的经济效益,对促进微电网的发展具有重要意义。
Research on intelligent dispatching of micro-grid according to optimized particle swarm algorithm
In the process of grid connection of irregular output micro-grid systems, it is of great research significance to make micro-grid scheduling operate more effectively and economically. To minimize the environmental and total operating costs of the micro-grid intelligent scheduling system during grid connection, this study proposes a micro-grid intelligent scheduling model based on an optimized particle swarm optimization algorithm. The optimized particle swarm algorithm mainly improves the problem of the particle swarm algorithm being prone to local optima, making it reduce the possibility of local convergence. Comparative tests were conducted on the improved IPSO algorithm, and the results showed that the non-dominated solution concentration pollution emissions obtained by the improved IPSO algorithm were at least 18326 Ib, which was lower than the comparison algorithm. In the empirical analysis of the intelligent scheduling model based on the improved IPSO algorithm, the convergence and satisfaction of the model were 0.0054 and 0.922, respectively, which were superior to the comparison algorithm. The above results indicate that the intelligent scheduling model for micro-grid based on the improved IPSO algorithm has good economy and stability. Compared with traditional energy dispatch methods, this energy dispatch mode has higher economic benefits and is of great significance for promoting the development of micro-grid.