Feasibility Identification and Computational Efficiency Improvement for Two-Stage RUC with Multiple Wind Farms
Date of Original Version
The increasing penetration level of wind power challenges robust unit commitment with feasibilities and high computational burden. To meet these challenges, we propose two-fold advances for the two-stage robust unit commitment (TS-RUC), aiming at providing feasible solution and efficient decision tool for the TS-RUC with multiple wind farms. First, the feasibility identification method is proposed to ensure the tractability of the TS-RUC. The feasibility boundaries are determined based on values of two sets of introduced slack variables, the wind power curtailment and load shedding. Second, the disjunctive programming is used to improve the computational efficiency of the max-min problem, which is reformulated with convex hull relaxation (CHR) method to reduce constraints embedding binary uncertainty variables. Simulation results on the modified IEEE-118 bus system and Henan power grid demonstrate that the proposed improvement for the TS-RUC can be implemented for power systems with multiple wind farms and significant wind power. The feasibility identification can guarantee a feasible solution and the use of the CHR can improve computational efficiency.
IEEE Transactions on Sustainable Energy
Zhang, Menglin, Jiakun Fang, Xiaomeng Ai, Hang Shuai, Wei Yao, Haibo He, Qiuwei Wu, and Jinyu Wen. "Feasibility Identification and Computational Efficiency Improvement for Two-Stage RUC with Multiple Wind Farms." IEEE Transactions on Sustainable Energy 11, 3 (2020): 1669-1678. doi:10.1109/TSTE.2019.2936581.