Optimization Method of Interprovincial Trading Plan for Surplus Renewable Energy Power Based on CVaR and Output Prediction

被引:0
|
作者
Cheng J. [1 ]
Yan Z. [1 ]
Li M. [2 ]
Yun J. [1 ]
Xu X. [1 ]
Wang H. [1 ]
机构
[1] Key Laboratory of Power Transmission and Conversion, Ministry of Education, Shanghai Jiao Tong University, Shanghai
[2] State Grid Corporation of China, Beijing
来源
基金
国家重点研发计划;
关键词
Conditional value-at-risk; Cross-regional electricity trading; Probabilistic prediction; Risk control; Spot trading; Stochastic optimization;
D O I
10.13336/j.1003-6520.hve.20201751
中图分类号
学科分类号
摘要
Interprovincial electricity spot trading of surplus renewable energy is an important way to overcome the inverse distribution of energy supply and demand in China and promote the consumption of renewable energy. In the existing researches, the surplus power prediction is calculated based on the renewable power prediction, and the prediction results are not very sensitive. Conventional optimization methods are difficult to deal with the high risks of low acuity to spot transactions. This paper applies conditional value-at-risk (CVaR) theory to quantify transaction risk, and proposes an automatic adjustment method of risk coefficients to achieve risk control, so as to find the optimal surplus power interprovincial transaction plan. Then, to get the minimum incremental network loss caused by the transactions, the optimization and decomposition model of the surplus power in the area is established, and the transaction plan is implemented to the power producers in the sending area. Finally, a case was studied by using historical data from a certain area to verify the effectiveness of the method. The results show that the proposed method can be adopted to effectively control the transaction risk and improve the economic benefits while ensuring the security of the power grid. © 2022, High Voltage Engineering Editorial Department of CEPRI. All right reserved.
引用
收藏
页码:467 / 476
页数:9
相关论文
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