{"title":"A Demand Side Response Optimization Model Considering the Output Characteristics of New Energy","authors":"Jiang Hu, Rui Ma, Ke-Yuan Qin, Wenxiang Liu, Wei Li, Haojie Deng","doi":"10.1109/CEEPE58418.2023.10166448","DOIUrl":null,"url":null,"abstract":"With the increasing proportion of new energy such as wind power and photovoltaic power generation, the traditional demand side response scheme is difficult to adapt to the high proportion of new energy systems. Based on this, a demand side response optimization method considering the output characteristics of new energy is proposed in this paper. First of all, according to the historical year's wind and solar output data, study the cluster effect of wind power and photovoltaic, and calculate the assurance rate of new energy in different confidence intervals on this basis. Then, analyze the multi time scale net load curves under different new energy penetration rates, establish the load time division probability model based on the fuzzy semi trapezoidal membership function, analyze the relationship between the new energy output characteristics and the net load distribution, and then establish the demand response optimization model considering the new energy output characteristics according to the elasticity coefficient matrix, which is solved by particle swarm optimization algorithm. Finally, the feasibility and effectiveness of this method are verified by comparing the calculation results of the current TOU price policy.","PeriodicalId":431552,"journal":{"name":"2023 6th International Conference on Energy, Electrical and Power Engineering (CEEPE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 6th International Conference on Energy, Electrical and Power Engineering (CEEPE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEEPE58418.2023.10166448","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
With the increasing proportion of new energy such as wind power and photovoltaic power generation, the traditional demand side response scheme is difficult to adapt to the high proportion of new energy systems. Based on this, a demand side response optimization method considering the output characteristics of new energy is proposed in this paper. First of all, according to the historical year's wind and solar output data, study the cluster effect of wind power and photovoltaic, and calculate the assurance rate of new energy in different confidence intervals on this basis. Then, analyze the multi time scale net load curves under different new energy penetration rates, establish the load time division probability model based on the fuzzy semi trapezoidal membership function, analyze the relationship between the new energy output characteristics and the net load distribution, and then establish the demand response optimization model considering the new energy output characteristics according to the elasticity coefficient matrix, which is solved by particle swarm optimization algorithm. Finally, the feasibility and effectiveness of this method are verified by comparing the calculation results of the current TOU price policy.