|XI Junye,TONG Xiaoyang,LI Zhi,DONG Xingxing,YANG Mingjie,LIU Fang.Low-carbon distributionally robust optimal scheduling for AC/DC distribution network considering wind power uncertainty[J].Electric Power Automation Equipment,2023,43(11):59-66
|关键词: 交直流配电网 Copula函数 风电不确定性 碳交易 分散协调 K-L散度 分布鲁棒调度
|Low-carbon distributionally robust optimal scheduling for AC/DC distribution network considering wind power uncertainty
XI Junye1, TONG Xiaoyang1, LI Zhi1, DONG Xingxing1, YANG Mingjie2, LIU Fang2
1.School of Electrical Engineering, Southwest Jiaotong University, Chengdu 611756, China;2.Jiaozuo Power Supply Company, State Grid Henan Electric Power Company, Jiaozuo 454150, China
|In order to increase the wind power absorption capacity of the distribution network and reduce the carbon emission, a low-carbon distributionally robust optimal scheduling model for AC/DC distribution network is established. The positive correlation between historical data of wind power forecast error and wind power forecast output is analyzed. The mixed Copula function is used to establish the joint probability distribution between them, and the conditional probability distribution of wind power forecast error is obtained. The AC/DC distribution network is decoupled as AC and DC subnets, taking the minimum comprehensive operating cost of each subnet as the optimization objective, and the carbon trading mechanism is introduced in the AC subnet optimization model, so that the decentralized coordinated optimization model of AC/DC distribution network is established. Taking the obtained conditional probability distribution of wind power forecast error as the reference, the distributionally robust ambiguous set based on K-L divergence is constructed. The proposed optimization model is converted into a single-layer optimization objective model by using Lagrange dualism theory and the alternating direction method of multipliers is used for decentralized coordination optimal solution. Simulative results based on the modified 33-bus AC/DC distribution network model show that the proposed model can effectively reduce the carbon emission at distribution side and significantly improve the consumption capacity of wind power.
|Key words: AC/DC distribution network Copula function wind power uncertainty carbon trading decentralized coordination K-L divergence distributionally robust scheduling