{"title":"Stochastic economic dispatch scheme with distributed loads using group search optimizer","authors":"Mengshi Li, Y. Hu, T. Ji, P. Wu","doi":"10.1109/ISGT-ASIA.2015.7386967","DOIUrl":null,"url":null,"abstract":"This paper proposed an economic dispatch scheme based on stochastic frame. Compared with conventional dispatch, the stochastic dispatch fully considers the variation of distributed load variations in the grid between dispatch intervals. The objective function of the stochastic dispatch scheme aims to minimize the distribution of fuel cost rather than a single value. Due to the stochastic analysis, the computational complexity of proposed method is also significantly increased. Therefore, this research adopts a animal behavior inspired algorithm, Group Search Optimizer (GSO) to solve the stochastic dispatch. The simulation studies are taken on the IEEE 30-bus system with uncertain load. The comparison between the results achieved using the proposed method and GA and PSO is presented to demonstrate the merits of GSO.","PeriodicalId":208739,"journal":{"name":"2015 IEEE Innovative Smart Grid Technologies - Asia (ISGT ASIA)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Innovative Smart Grid Technologies - Asia (ISGT ASIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISGT-ASIA.2015.7386967","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper proposed an economic dispatch scheme based on stochastic frame. Compared with conventional dispatch, the stochastic dispatch fully considers the variation of distributed load variations in the grid between dispatch intervals. The objective function of the stochastic dispatch scheme aims to minimize the distribution of fuel cost rather than a single value. Due to the stochastic analysis, the computational complexity of proposed method is also significantly increased. Therefore, this research adopts a animal behavior inspired algorithm, Group Search Optimizer (GSO) to solve the stochastic dispatch. The simulation studies are taken on the IEEE 30-bus system with uncertain load. The comparison between the results achieved using the proposed method and GA and PSO is presented to demonstrate the merits of GSO.