Bivariate Stochastic Optimization Model for Bidding Strategies Considering Competition Among Renewable Power Producers  

作　　者：Jifeng Cheng Zheng Yan Xiaoyuan Xu Han Wang Yan Zhang Shuying Zhang 

机构地区：[1]Department of Electrical Engineering,Shanghai Jiao Tong University,Shanghai 200240,China

出　　处：《CSEE Journal of Power and Energy Systems》2024年第6期2539-2550,共12页中国电机工程学会电力与能源系统学报（英文）

基　　金：supported by National Key R&D Program of China(Technology and application of wind power/photovoltaic power prediction for promoting renewable energy consumption,2018YFB0904200);Eponymous Complement S&T Program of State Grid Corporation of China(SGLNDKOOKJJS1800266)。

摘　　要：The competition among renewable power producers(RPPs)may cause the cleared power of RPPs to be less than the bidding power,while the impact of competition is neglected in the existing price-taker methods.To overcome the above deficiency,this paper develops an optimal bidding strategy,considering the competition among RPPs.First,a bivariate stochastic optimization(BSO)model for a bidding strategy is proposed by considering the variable power output of RPPs and the competition among RPPs.Particularly,the cleared power estimated by the demand-supply ratio is a random variable in the proposed BSO model.Then,the Newton method and particle swarm optimization(PSO)are combined to solve the BSO model in which various probability distribution functions(PDFs)of renewable energy generation are considered.Finally,the effectiveness of the proposed method is verified based on the results of a case study,which shows that the proposed model performed better than the traditional chance-constrained programming(CCP)model in power market competition.

关 键 词：Bidding strategy power market power producer renewable energy generation stochastic optimization 

分 类 号：TK01[动力工程及工程热物理]