Shumin Sun, Peng Yu, Jiawei Xing, Yuejiao Wang, Song Yang
{"title":"基于改进粒子群优化算法的主动配电网运行多目标协同优化。","authors":"Shumin Sun, Peng Yu, Jiawei Xing, Yuejiao Wang, Song Yang","doi":"10.1038/s41598-025-90907-2","DOIUrl":null,"url":null,"abstract":"<p><p>ADN (Active distribution network) is easily disturbed during its operation, resulting in problems such as power supply quality degradation and operation safety deterioration. Therefore, the research and simulation of multi-objective collaborative optimization of ADN operation based on improved particle swarm optimization algorithm are proposed. An objective function of multi-objective collaborative optimization configuration for ADN operation is constructed. According to this objective function, the improved particle swarm optimization algorithm is used to optimize the collaborative optimization configuration, and the population particles are mutated, and the obtained result is the optimal energy storage capacity configuration result of power system. The architecture of the simulation platform for cooperative operation of ADN is constructed, and the load grades of distribution system are divided. Based on the hierarchical management of loads in distributed systems, multi-objective collaborative optimization of ADN operating voltage in both frequency and time domains has been achieved. The experimental results show that during peak periods, the system's load capacity is only twice that of before optimization or other situations, achieving stable power supply for peak power demand. Multi-objective collaborative optimization in frequency domain and time domain has the best effect. Under the conditions of reactive power and active power, the multi-objective collaborative optimization method of ADN operation has good results.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"8999"},"PeriodicalIF":3.9000,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11910578/pdf/","citationCount":"0","resultStr":"{\"title\":\"Multi-objective collaborative optimization of active distribution network operation based on improved particle swarm optimization algorithm.\",\"authors\":\"Shumin Sun, Peng Yu, Jiawei Xing, Yuejiao Wang, Song Yang\",\"doi\":\"10.1038/s41598-025-90907-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>ADN (Active distribution network) is easily disturbed during its operation, resulting in problems such as power supply quality degradation and operation safety deterioration. Therefore, the research and simulation of multi-objective collaborative optimization of ADN operation based on improved particle swarm optimization algorithm are proposed. An objective function of multi-objective collaborative optimization configuration for ADN operation is constructed. According to this objective function, the improved particle swarm optimization algorithm is used to optimize the collaborative optimization configuration, and the population particles are mutated, and the obtained result is the optimal energy storage capacity configuration result of power system. The architecture of the simulation platform for cooperative operation of ADN is constructed, and the load grades of distribution system are divided. Based on the hierarchical management of loads in distributed systems, multi-objective collaborative optimization of ADN operating voltage in both frequency and time domains has been achieved. The experimental results show that during peak periods, the system's load capacity is only twice that of before optimization or other situations, achieving stable power supply for peak power demand. Multi-objective collaborative optimization in frequency domain and time domain has the best effect. Under the conditions of reactive power and active power, the multi-objective collaborative optimization method of ADN operation has good results.</p>\",\"PeriodicalId\":21811,\"journal\":{\"name\":\"Scientific Reports\",\"volume\":\"15 1\",\"pages\":\"8999\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2025-03-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11910578/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific Reports\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1038/s41598-025-90907-2\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Reports","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41598-025-90907-2","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
Multi-objective collaborative optimization of active distribution network operation based on improved particle swarm optimization algorithm.
ADN (Active distribution network) is easily disturbed during its operation, resulting in problems such as power supply quality degradation and operation safety deterioration. Therefore, the research and simulation of multi-objective collaborative optimization of ADN operation based on improved particle swarm optimization algorithm are proposed. An objective function of multi-objective collaborative optimization configuration for ADN operation is constructed. According to this objective function, the improved particle swarm optimization algorithm is used to optimize the collaborative optimization configuration, and the population particles are mutated, and the obtained result is the optimal energy storage capacity configuration result of power system. The architecture of the simulation platform for cooperative operation of ADN is constructed, and the load grades of distribution system are divided. Based on the hierarchical management of loads in distributed systems, multi-objective collaborative optimization of ADN operating voltage in both frequency and time domains has been achieved. The experimental results show that during peak periods, the system's load capacity is only twice that of before optimization or other situations, achieving stable power supply for peak power demand. Multi-objective collaborative optimization in frequency domain and time domain has the best effect. Under the conditions of reactive power and active power, the multi-objective collaborative optimization method of ADN operation has good results.
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