DOI:10.35833/MPCE.2020.000937 Short-term Transmission Maintenance Scheduling Considering Network Topology Optimization Page view: 79        Net amount: 126 Author: Weixin Zhang,Bo Hu,Kaigui Xie,Changzheng Shao,Tao Niu,Jiahao Yan,Lvbin Peng,Maosen Cao,Yue Sun Author Affiliation: with the State Key Laboratory of Power Transmission Equipment & System Security and New Technology at Chongqing University, Chongqing 400044, China Foundation: This work was supported by the National Key R&D Program of China “Technology and application of wind power/photovoltaic power prediction for promoting renewable energy consumption” (No. 2018YFB0904200) and eponymous Complement S&T Program of State Grid Corporation of China (No. SGLNDKOOKJJS1800266). Abstract: With the increasing penetration of renewable energy sources, transmission maintenance scheduling (TMS) will have a larger impact on the accommodation of wind power. Meanwhile, the more flexible transmission network topology owing to the network topology optimization (NTO) technique can ensure the secure and economic operation of power systems. This paper proposes a TMS model considering NTO to decrease the wind curtailment without adding control devices. The problem is formulated as a two-stage stochastic mixed-integer programming model. The first stage arranges the maintenance periods of transmission lines. The second stage optimizes the transmission network topology to minimize the maintenance cost and system operation in different wind speed scenarios. The proposed model cannot be solved efficiently with off-the-shelf solvers due to the binary variables in both stages. Therefore, the progressive hedging algorithm is applied. The results on the modified IEEE RTS-79 system show that the proposed method can reduce the negative impact of transmission maintenance on wind accommodation by 65.49%, which proves its effectiveness. Keywords: Mixed-integer linear programming ; network topology optimization ; progressive hedging algorithm ; stochastic optimization ; transmission maintenance scheduling ; wind curtailment Received:October 28, 2020               Online Time:2022/07/15 View Full Text       Download reader