{"title":"配电网损耗与拥塞缓解的多目标联合启发式- spso算法","authors":"C. Iraklis","doi":"10.1109/energycon53164.2022.9830303","DOIUrl":null,"url":null,"abstract":"Renewable energy sources and distributed power generation units already have an important role in electrical power generation. A mixture of different technologies penetrating the electrical grid, adds complexity in the management of distribution networks. High penetration of distributed generation (DG) units creates node over-voltages, increased power losses, unreliable power management, reverse power flow and congestion. This paper presents an optimization algorithm capable of reducing congestion and power losses, both described as a function of weighted sum. Two factors that describe congestion are being proposed. An upgraded selective particle swarm optimization algorithm (SPSO) is used as a solution focusing on the technique of network reconfiguration. T he u pgraded S PSO a lgorithm is achieved with the addition of a heuristic algorithm specializing in reduction of power losses, with several scenarios being simulated. Results show significant i mprovement in m inimization of losses and congestion while achieving very small calculation times.","PeriodicalId":106388,"journal":{"name":"2022 IEEE 7th International Energy Conference (ENERGYCON)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-objective Combined Heuristic-SPSO for Power Loss and Congestion Mitigation in Distribution Networks\",\"authors\":\"C. Iraklis\",\"doi\":\"10.1109/energycon53164.2022.9830303\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Renewable energy sources and distributed power generation units already have an important role in electrical power generation. A mixture of different technologies penetrating the electrical grid, adds complexity in the management of distribution networks. High penetration of distributed generation (DG) units creates node over-voltages, increased power losses, unreliable power management, reverse power flow and congestion. This paper presents an optimization algorithm capable of reducing congestion and power losses, both described as a function of weighted sum. Two factors that describe congestion are being proposed. An upgraded selective particle swarm optimization algorithm (SPSO) is used as a solution focusing on the technique of network reconfiguration. T he u pgraded S PSO a lgorithm is achieved with the addition of a heuristic algorithm specializing in reduction of power losses, with several scenarios being simulated. Results show significant i mprovement in m inimization of losses and congestion while achieving very small calculation times.\",\"PeriodicalId\":106388,\"journal\":{\"name\":\"2022 IEEE 7th International Energy Conference (ENERGYCON)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 7th International Energy Conference (ENERGYCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/energycon53164.2022.9830303\",\"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 7th International Energy Conference (ENERGYCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/energycon53164.2022.9830303","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-objective Combined Heuristic-SPSO for Power Loss and Congestion Mitigation in Distribution Networks
Renewable energy sources and distributed power generation units already have an important role in electrical power generation. A mixture of different technologies penetrating the electrical grid, adds complexity in the management of distribution networks. High penetration of distributed generation (DG) units creates node over-voltages, increased power losses, unreliable power management, reverse power flow and congestion. This paper presents an optimization algorithm capable of reducing congestion and power losses, both described as a function of weighted sum. Two factors that describe congestion are being proposed. An upgraded selective particle swarm optimization algorithm (SPSO) is used as a solution focusing on the technique of network reconfiguration. T he u pgraded S PSO a lgorithm is achieved with the addition of a heuristic algorithm specializing in reduction of power losses, with several scenarios being simulated. Results show significant i mprovement in m inimization of losses and congestion while achieving very small calculation times.