Farhad Pouladi, Amir Mohammad Gilani, Bahareh Nikpour, H. Salehinejad
{"title":"Optimum Localization of Wind Turbine Sites Using Opposition Based Ant Colony Optimization","authors":"Farhad Pouladi, Amir Mohammad Gilani, Bahareh Nikpour, H. Salehinejad","doi":"10.1109/DeSE.2013.13","DOIUrl":null,"url":null,"abstract":"With recent increase in energy consumption as well as reduction of fossil fuels, employing new methods for generation of green energy in smart grids, such as wind energy, is of great interest for governments. That is why expanding of wind turbine farms is a priority in many countries. One of the most important parameters in design and implementation of such farms is optimum selection of wind turbine farm location in a way that the corresponding constraints are met. This paper introduces a new optimization algorithm based on the opposition based ant colony optimization (OACO) algorithm for this aim. Analyzes of simulation results demonstrate performance of the proposed method for optimum localization of wind turbine farms in Saudi Arabia case study.","PeriodicalId":248716,"journal":{"name":"2013 Sixth International Conference on Developments in eSystems Engineering","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Sixth International Conference on Developments in eSystems Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DeSE.2013.13","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
With recent increase in energy consumption as well as reduction of fossil fuels, employing new methods for generation of green energy in smart grids, such as wind energy, is of great interest for governments. That is why expanding of wind turbine farms is a priority in many countries. One of the most important parameters in design and implementation of such farms is optimum selection of wind turbine farm location in a way that the corresponding constraints are met. This paper introduces a new optimization algorithm based on the opposition based ant colony optimization (OACO) algorithm for this aim. Analyzes of simulation results demonstrate performance of the proposed method for optimum localization of wind turbine farms in Saudi Arabia case study.