{"title":"Clearing Model of New Energy Power Market Based on Carbon Emission Reward and Punishment Factor","authors":"Liu Junmin, Bao Guangqing, Hao Ruhai, Zhou Zhiyi","doi":"10.1109/PSET56192.2022.10100475","DOIUrl":null,"url":null,"abstract":"In order to alleviate the increasingly serious environment pollution and energy crisis, renewable energy sources are increasingly participated in power market and a reasonable power spot clearing model is one of the feasible ways to solving the problem of massive wind and photovoltaic power curtailment and achieving the goal of carbon peaking and carbon neutrality. In this paper, the carbon emission index is incorporated into the trading mechanism of power market, and a novel energy regional clearing model (RCM) based on carbon emission reward and punishment factor (CERPF) is proposed. Firstly, on account of the principle of environmental regulation, the reward and punishment of carbon emission is regarded as a market intervention measure to improve the consumption of new energy, and incorporated into the cost objective function, in which, use two-stage dynamic step-size revision method to optimization CERPF, so as to form a positive relationship between new energy consumption and carbon emission reduction. Secondly, according to the goal of maximizing social welfare, the single time-Locational Marginal Price (s-LMP) is calculated, and then the buses are clustered into regions used improved K-means algorithm which can determine the initial cluster center and reflect geographical location to form RCM, it can simplifies the calculation of the traditional locational clearing model (LCM). Finally, to simulate the power system with high proportion of new energy in Gansu of China, the clearing model proposed here is verified based on the changed IEEE118 bus system. It conclude that the relative error between locational electricity price (LMP) and regional marginal price (RMP) is small, and RMP is consistent with the reality.","PeriodicalId":402897,"journal":{"name":"2022 IEEE International Conference on Power Systems and Electrical Technology (PSET)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Power Systems and Electrical Technology (PSET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PSET56192.2022.10100475","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 order to alleviate the increasingly serious environment pollution and energy crisis, renewable energy sources are increasingly participated in power market and a reasonable power spot clearing model is one of the feasible ways to solving the problem of massive wind and photovoltaic power curtailment and achieving the goal of carbon peaking and carbon neutrality. In this paper, the carbon emission index is incorporated into the trading mechanism of power market, and a novel energy regional clearing model (RCM) based on carbon emission reward and punishment factor (CERPF) is proposed. Firstly, on account of the principle of environmental regulation, the reward and punishment of carbon emission is regarded as a market intervention measure to improve the consumption of new energy, and incorporated into the cost objective function, in which, use two-stage dynamic step-size revision method to optimization CERPF, so as to form a positive relationship between new energy consumption and carbon emission reduction. Secondly, according to the goal of maximizing social welfare, the single time-Locational Marginal Price (s-LMP) is calculated, and then the buses are clustered into regions used improved K-means algorithm which can determine the initial cluster center and reflect geographical location to form RCM, it can simplifies the calculation of the traditional locational clearing model (LCM). Finally, to simulate the power system with high proportion of new energy in Gansu of China, the clearing model proposed here is verified based on the changed IEEE118 bus system. It conclude that the relative error between locational electricity price (LMP) and regional marginal price (RMP) is small, and RMP is consistent with the reality.