{"title":"Power Transaction Game Algorithm with Micro Grid Based on Residual Regression Model","authors":"Hongjie Li","doi":"10.1093/ijlct/ctad031","DOIUrl":null,"url":null,"abstract":"\n Direct transaction between microgrid and distribution network is the most common market transaction mode. With the rapid expansion of business scale, industry development and diversification of service types, it is easy to cause problems such as opaque transaction data between users and easy tampering of transaction data. In order to improve the trading ability of power market in microgrid group, a game algorithm of power trading with microgrid based on residual regression model is proposed. According to the power quality level and power sales strategy, a residual regression model is established to balance the characteristic quantity of electricity price. The quadratic function is used to solve the optimal selling strategy of power sales companies, and the threshold of equilibrium solution is analyzed. The supply and demand model of microgrid is established to optimize the decision variables of electricity price in power sales companies, and the fitness value is obtained by particle swarm optimization. The bidding strategy game model of microgrid power sales company is constructed, and the rules of power transaction settlement are set to realize the transaction settlement between microgrid and distribution network. The experimental results show that the electricity price is stable, the comprehensive income is high, the user income and cost income are moderate, and the profit is high. Thus, it is proved that the proposed method is economical and effective, and the economy of electric energy use is guaranteed while fully considering the self-interest of microgrid.","PeriodicalId":14118,"journal":{"name":"International Journal of Low-carbon Technologies","volume":" ","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Low-carbon Technologies","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1093/ijlct/ctad031","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
Direct transaction between microgrid and distribution network is the most common market transaction mode. With the rapid expansion of business scale, industry development and diversification of service types, it is easy to cause problems such as opaque transaction data between users and easy tampering of transaction data. In order to improve the trading ability of power market in microgrid group, a game algorithm of power trading with microgrid based on residual regression model is proposed. According to the power quality level and power sales strategy, a residual regression model is established to balance the characteristic quantity of electricity price. The quadratic function is used to solve the optimal selling strategy of power sales companies, and the threshold of equilibrium solution is analyzed. The supply and demand model of microgrid is established to optimize the decision variables of electricity price in power sales companies, and the fitness value is obtained by particle swarm optimization. The bidding strategy game model of microgrid power sales company is constructed, and the rules of power transaction settlement are set to realize the transaction settlement between microgrid and distribution network. The experimental results show that the electricity price is stable, the comprehensive income is high, the user income and cost income are moderate, and the profit is high. Thus, it is proved that the proposed method is economical and effective, and the economy of electric energy use is guaranteed while fully considering the self-interest of microgrid.
期刊介绍:
The International Journal of Low-Carbon Technologies is a quarterly publication concerned with the challenge of climate change and its effects on the built environment and sustainability. The Journal publishes original, quality research papers on issues of climate change, sustainable development and the built environment related to architecture, building services engineering, civil engineering, building engineering, urban design and other disciplines. It features in-depth articles, technical notes, review papers, book reviews and special issues devoted to international conferences. The journal encourages submissions related to interdisciplinary research in the built environment. The journal is available in paper and electronic formats. All articles are peer-reviewed by leading experts in the field.