{"title":"Multi-Objective Optimal Bidding Approach for both Small & Large Customers in Competitive power Market","authors":"Manisha Saini, Ajay Bhardwaj, Sarfaraz Nawaz","doi":"10.1109/I2CT57861.2023.10126351","DOIUrl":null,"url":null,"abstract":"In the present scenario of the electricity energy market, power generation firms seek to maximize revenue by optimizing the bid in the electricity market. In a competitive market, Strategic bidding allows each participant to improve his individual profit; however, this has a detrimental effect on public benefit. This study presents a mechanism for developing a strategic bid for electricity producers and users in a pool co-style energy market. The system is dispatched to maximize social welfare, with each supplier/large consumer bidding a linear supply/demand function. Price takers require a proper bidding structure to identify the best bidding tactics. As a result, the model must be thought of as a two-level optimization issue. Price takers submit strategic bids to the Independent System Operator (ISO) at the lower level, while the ISO Market Clearing Price (MCP) is used to maximize social welfare at the upper level in a day-ahead power market to maximize social welfare at the upper level using a pay-as-bid mechanism in a sealed auction in the competitive power market. On the IEEE-30 bus system, the proposed method's efficiency was tested. Four different evolutionary algorithms such as NSGA-II, NSGA-III, MOGWO, and MOPSO were used to address the problem from two separate perspectives for solving proposed multi-objective problems. The result section presents a comparative analysis of the total profit and market clearing price, showing that the NSGA-III algorithm offers superior results than other methods.","PeriodicalId":150346,"journal":{"name":"2023 IEEE 8th International Conference for Convergence in Technology (I2CT)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE 8th International Conference for Convergence in Technology (I2CT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/I2CT57861.2023.10126351","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
In the present scenario of the electricity energy market, power generation firms seek to maximize revenue by optimizing the bid in the electricity market. In a competitive market, Strategic bidding allows each participant to improve his individual profit; however, this has a detrimental effect on public benefit. This study presents a mechanism for developing a strategic bid for electricity producers and users in a pool co-style energy market. The system is dispatched to maximize social welfare, with each supplier/large consumer bidding a linear supply/demand function. Price takers require a proper bidding structure to identify the best bidding tactics. As a result, the model must be thought of as a two-level optimization issue. Price takers submit strategic bids to the Independent System Operator (ISO) at the lower level, while the ISO Market Clearing Price (MCP) is used to maximize social welfare at the upper level in a day-ahead power market to maximize social welfare at the upper level using a pay-as-bid mechanism in a sealed auction in the competitive power market. On the IEEE-30 bus system, the proposed method's efficiency was tested. Four different evolutionary algorithms such as NSGA-II, NSGA-III, MOGWO, and MOPSO were used to address the problem from two separate perspectives for solving proposed multi-objective problems. The result section presents a comparative analysis of the total profit and market clearing price, showing that the NSGA-III algorithm offers superior results than other methods.