Mintong Zhao, Jia-jia Huan, Xin Huang, Tao Yu, Qiaoyi Ding
{"title":"基于非洲秃鹫优化算法的分布式发电优化规划","authors":"Mintong Zhao, Jia-jia Huan, Xin Huang, Tao Yu, Qiaoyi Ding","doi":"10.1109/EI256261.2022.10116298","DOIUrl":null,"url":null,"abstract":"With the continuous impact of environmental pollution, the traditional generator represented by fossil fuels is gradually being replaced by renewable energy generators. Different from the conventional optimal planning, which only includes photovoltaic (PV) and wind turbines. This paper adds the use of fuel cells (FC) and miniature steam turbines with PV systems and wind turbines, which can make up for the defect of fluctuation of its output power. In addition, a multi-objective model considering power loss, voltage profile, and investment cost is established and solved by the African vultures optimization algorithm (AVOA). Finally, the simulation is based on IEEE 33 and 69 node distribution network (DN) systems. The results show that AVOA has a fast convergence speed and strong optimization characteristics, and can improve voltage distribution after distributed generation (DG) access. The simulation results show that the power loss and voltage profile decreased by 57% and 58% at the IEEE 33 and 64% and 61% at the IEEE 69 node after being connected to DG.","PeriodicalId":413409,"journal":{"name":"2022 IEEE 6th Conference on Energy Internet and Energy System Integration (EI2)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Optimal Planning of Distributed Generation Based on African Vultures Optimization Algorithm\",\"authors\":\"Mintong Zhao, Jia-jia Huan, Xin Huang, Tao Yu, Qiaoyi Ding\",\"doi\":\"10.1109/EI256261.2022.10116298\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the continuous impact of environmental pollution, the traditional generator represented by fossil fuels is gradually being replaced by renewable energy generators. Different from the conventional optimal planning, which only includes photovoltaic (PV) and wind turbines. This paper adds the use of fuel cells (FC) and miniature steam turbines with PV systems and wind turbines, which can make up for the defect of fluctuation of its output power. In addition, a multi-objective model considering power loss, voltage profile, and investment cost is established and solved by the African vultures optimization algorithm (AVOA). Finally, the simulation is based on IEEE 33 and 69 node distribution network (DN) systems. The results show that AVOA has a fast convergence speed and strong optimization characteristics, and can improve voltage distribution after distributed generation (DG) access. The simulation results show that the power loss and voltage profile decreased by 57% and 58% at the IEEE 33 and 64% and 61% at the IEEE 69 node after being connected to DG.\",\"PeriodicalId\":413409,\"journal\":{\"name\":\"2022 IEEE 6th Conference on Energy Internet and Energy System Integration (EI2)\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 6th Conference on Energy Internet and Energy System Integration (EI2)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EI256261.2022.10116298\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 6th Conference on Energy Internet and Energy System Integration (EI2)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EI256261.2022.10116298","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal Planning of Distributed Generation Based on African Vultures Optimization Algorithm
With the continuous impact of environmental pollution, the traditional generator represented by fossil fuels is gradually being replaced by renewable energy generators. Different from the conventional optimal planning, which only includes photovoltaic (PV) and wind turbines. This paper adds the use of fuel cells (FC) and miniature steam turbines with PV systems and wind turbines, which can make up for the defect of fluctuation of its output power. In addition, a multi-objective model considering power loss, voltage profile, and investment cost is established and solved by the African vultures optimization algorithm (AVOA). Finally, the simulation is based on IEEE 33 and 69 node distribution network (DN) systems. The results show that AVOA has a fast convergence speed and strong optimization characteristics, and can improve voltage distribution after distributed generation (DG) access. The simulation results show that the power loss and voltage profile decreased by 57% and 58% at the IEEE 33 and 64% and 61% at the IEEE 69 node after being connected to DG.