{"title":"Profit Maximization Bidding Strategy for a GENCO using Whale Optimization Algorithm","authors":"P. Jain, Akash Saxena","doi":"10.1109/WITCONECE48374.2019.9092917","DOIUrl":null,"url":null,"abstract":"In a deregulated environment of electricity mar- ket,all participants of this market have intentions to increase their profit as much as possible in absentia of their competitor’s bid prices. These optimal Bidding strategies are first obtained through some conventional methods but In a recent trend of meta-heuristic approaches,this stochastic optimization problem solved through different meta-heuristic approaches. Due to the popularity of stochastic optimization techniques. deterministic approaches are obsolete due to their inefficiency of solving this bidding problem. In the same line of order, This paper presents the application of recent meta heuristic approach namely, Whale Optimization Algorithm (WOA) to solve strategic bidding problem of a test system having 6 competitors and MCP and profit is obtained after optimization routine. The results confirms the supremacy of WOA over other meta-heuristic approaches.","PeriodicalId":350816,"journal":{"name":"2019 Women Institute of Technology Conference on Electrical and Computer Engineering (WITCON ECE)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Women Institute of Technology Conference on Electrical and Computer Engineering (WITCON ECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WITCONECE48374.2019.9092917","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In a deregulated environment of electricity mar- ket,all participants of this market have intentions to increase their profit as much as possible in absentia of their competitor’s bid prices. These optimal Bidding strategies are first obtained through some conventional methods but In a recent trend of meta-heuristic approaches,this stochastic optimization problem solved through different meta-heuristic approaches. Due to the popularity of stochastic optimization techniques. deterministic approaches are obsolete due to their inefficiency of solving this bidding problem. In the same line of order, This paper presents the application of recent meta heuristic approach namely, Whale Optimization Algorithm (WOA) to solve strategic bidding problem of a test system having 6 competitors and MCP and profit is obtained after optimization routine. The results confirms the supremacy of WOA over other meta-heuristic approaches.