{"title":"不平衡配电系统的最优调度与实时电压控制方法","authors":"Z. Ziadi, M. Abdel-Akher","doi":"10.1109/ICIT.2014.6894958","DOIUrl":null,"url":null,"abstract":"This paper presents an optimal scheduling and real time voltage control of tap changing transformers and converters interfaced with Distributed Generators (DGs) in unbalanced three-phase distribution systems. The DGs considered in this paper are supposed to be Photovoltaic (PV) generators, due to the growing demand of renewable energies. However, high penetration of DGs may cause considerable voltage fluctuations and deviations from the statutory limits. Thus, based on predicted values of load demand and PV generation, a set of voltage references of tap transformers and DGs is optimized, using Genetic Algorithms (GA) optimization method, to reduce the losses while keeping the distribution voltage within an acceptable range. For that, the three phase power flow equations, which must be satisfied, are solved using Newton-Raphson method. The voltage control references are optimized for every preset period of time. However, in the meanwhile the voltage may fluctuate due to the PV power nature. Thus, a real time voltage control is applied on the DGs inverters exploiting their available reactive power based on the voltage drop. According to local voltage measurements at each node containing DG, fuzzy logic controllers adjust the voltage references of the optimal schedule. Twenty-four-hour data are used to simulate a 14-bus distribution system with unbalanced three-phase loads in 6 nodes to verify the effectiveness of the method.","PeriodicalId":240337,"journal":{"name":"2014 IEEE International Conference on Industrial Technology (ICIT)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Optimal scheduling and real time voltage control method for unbalanced distribution systems\",\"authors\":\"Z. Ziadi, M. Abdel-Akher\",\"doi\":\"10.1109/ICIT.2014.6894958\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an optimal scheduling and real time voltage control of tap changing transformers and converters interfaced with Distributed Generators (DGs) in unbalanced three-phase distribution systems. The DGs considered in this paper are supposed to be Photovoltaic (PV) generators, due to the growing demand of renewable energies. However, high penetration of DGs may cause considerable voltage fluctuations and deviations from the statutory limits. Thus, based on predicted values of load demand and PV generation, a set of voltage references of tap transformers and DGs is optimized, using Genetic Algorithms (GA) optimization method, to reduce the losses while keeping the distribution voltage within an acceptable range. For that, the three phase power flow equations, which must be satisfied, are solved using Newton-Raphson method. The voltage control references are optimized for every preset period of time. However, in the meanwhile the voltage may fluctuate due to the PV power nature. Thus, a real time voltage control is applied on the DGs inverters exploiting their available reactive power based on the voltage drop. According to local voltage measurements at each node containing DG, fuzzy logic controllers adjust the voltage references of the optimal schedule. Twenty-four-hour data are used to simulate a 14-bus distribution system with unbalanced three-phase loads in 6 nodes to verify the effectiveness of the method.\",\"PeriodicalId\":240337,\"journal\":{\"name\":\"2014 IEEE International Conference on Industrial Technology (ICIT)\",\"volume\":\"77 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE International Conference on Industrial Technology (ICIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIT.2014.6894958\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Conference on Industrial Technology (ICIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIT.2014.6894958","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal scheduling and real time voltage control method for unbalanced distribution systems
This paper presents an optimal scheduling and real time voltage control of tap changing transformers and converters interfaced with Distributed Generators (DGs) in unbalanced three-phase distribution systems. The DGs considered in this paper are supposed to be Photovoltaic (PV) generators, due to the growing demand of renewable energies. However, high penetration of DGs may cause considerable voltage fluctuations and deviations from the statutory limits. Thus, based on predicted values of load demand and PV generation, a set of voltage references of tap transformers and DGs is optimized, using Genetic Algorithms (GA) optimization method, to reduce the losses while keeping the distribution voltage within an acceptable range. For that, the three phase power flow equations, which must be satisfied, are solved using Newton-Raphson method. The voltage control references are optimized for every preset period of time. However, in the meanwhile the voltage may fluctuate due to the PV power nature. Thus, a real time voltage control is applied on the DGs inverters exploiting their available reactive power based on the voltage drop. According to local voltage measurements at each node containing DG, fuzzy logic controllers adjust the voltage references of the optimal schedule. Twenty-four-hour data are used to simulate a 14-bus distribution system with unbalanced three-phase loads in 6 nodes to verify the effectiveness of the method.