John Edward A. Abutin, Henrich T. Jovena, Robin Paul L. Trinidad, M. Pacis, G. Magwili
{"title":"基于遗传算法的混合配电发电机优化配置增强电压分布","authors":"John Edward A. Abutin, Henrich T. Jovena, Robin Paul L. Trinidad, M. Pacis, G. Magwili","doi":"10.1109/TENSYMP52854.2021.9550767","DOIUrl":null,"url":null,"abstract":"Placing Distributed Generator (DG) plays an important role in electric power systems as it reduces power losses and increases the voltage profiles. It is also important to take note that aside from placing DGs in the system, it is also important to locate its optimum position because the wrong placement of DGs can result to further power losses and voltage profile violation. This paper presents three cases for the study of the IEEE – 33 Bus system. A genetic algorithm was used as the optimization technique. In this test case, we used the 33-bus as the base case, while the other cases are putting a 0.29MW solar, 0.10MW wind, and lastly combining the 0.29MW solar and 0.10MW wind at the end of the simulation the case that has the lowest percent loss is the Hybrid system with Solar and Wind, which has 95.2092 percentage loss.","PeriodicalId":137485,"journal":{"name":"2021 IEEE Region 10 Symposium (TENSYMP)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Voltage Profile Enhancement by Optimal Placement of Hybrid Distribution Generators using Genetic Algorithm\",\"authors\":\"John Edward A. Abutin, Henrich T. Jovena, Robin Paul L. Trinidad, M. Pacis, G. Magwili\",\"doi\":\"10.1109/TENSYMP52854.2021.9550767\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Placing Distributed Generator (DG) plays an important role in electric power systems as it reduces power losses and increases the voltage profiles. It is also important to take note that aside from placing DGs in the system, it is also important to locate its optimum position because the wrong placement of DGs can result to further power losses and voltage profile violation. This paper presents three cases for the study of the IEEE – 33 Bus system. A genetic algorithm was used as the optimization technique. In this test case, we used the 33-bus as the base case, while the other cases are putting a 0.29MW solar, 0.10MW wind, and lastly combining the 0.29MW solar and 0.10MW wind at the end of the simulation the case that has the lowest percent loss is the Hybrid system with Solar and Wind, which has 95.2092 percentage loss.\",\"PeriodicalId\":137485,\"journal\":{\"name\":\"2021 IEEE Region 10 Symposium (TENSYMP)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE Region 10 Symposium (TENSYMP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TENSYMP52854.2021.9550767\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE Region 10 Symposium (TENSYMP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TENSYMP52854.2021.9550767","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Voltage Profile Enhancement by Optimal Placement of Hybrid Distribution Generators using Genetic Algorithm
Placing Distributed Generator (DG) plays an important role in electric power systems as it reduces power losses and increases the voltage profiles. It is also important to take note that aside from placing DGs in the system, it is also important to locate its optimum position because the wrong placement of DGs can result to further power losses and voltage profile violation. This paper presents three cases for the study of the IEEE – 33 Bus system. A genetic algorithm was used as the optimization technique. In this test case, we used the 33-bus as the base case, while the other cases are putting a 0.29MW solar, 0.10MW wind, and lastly combining the 0.29MW solar and 0.10MW wind at the end of the simulation the case that has the lowest percent loss is the Hybrid system with Solar and Wind, which has 95.2092 percentage loss.