{"title":"Multi objective optimal power flow to minimize losses and carbon emission using Wolf Algorithm","authors":"Yun Tonce Kusuma Priyanto, Lukman Hendarwin","doi":"10.1109/ISITIA.2015.7219971","DOIUrl":null,"url":null,"abstract":"The population growth and technological advances lead to increasing demand for electrical energy is not matched by the growth of energy sources. Many ways in which to distribute electrical energy with a variety of methods to get the amount of energy efficient with an economical price. In this paper would like to introduce applications use Wolf Algorithm (WA) for optimal settings on optimal power flow control variables. The main objective was tested and tried in the standard IEEE 30-bus test system with multi objective which showed losses and carbon emission value. The results of the main goals will be compared and reported in the literature. The results are quite promising and show effectiveness and resilience of the main goal.","PeriodicalId":124449,"journal":{"name":"2015 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Seminar on Intelligent Technology and Its Applications (ISITIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISITIA.2015.7219971","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
The population growth and technological advances lead to increasing demand for electrical energy is not matched by the growth of energy sources. Many ways in which to distribute electrical energy with a variety of methods to get the amount of energy efficient with an economical price. In this paper would like to introduce applications use Wolf Algorithm (WA) for optimal settings on optimal power flow control variables. The main objective was tested and tried in the standard IEEE 30-bus test system with multi objective which showed losses and carbon emission value. The results of the main goals will be compared and reported in the literature. The results are quite promising and show effectiveness and resilience of the main goal.