Subjects: Dynamic and Electric Engineering >> Electrical Engineering submitted time 2022-10-11
Abstract： The temporary overvoltage (TOV) during fault recovery process of renewable energy system seriously restricts the development of renewable energy. However, the existing research lacks quantitative indicators of the TOV. Therefore, based on the mechanism of TOV, this paper proposes a method to quantify the TOV risk of multiple renewable energy station system (MRESS) considering the reactive power saturation characteristic. Firstly, based on the TOV mechanism of MRESS, the analysis model under different factors during fault recovery is established, and then the rationality of TOV assessment based on phasor model is demonstrated. After fully considering the saturation characteristics of converters after fault and the interaction between renewable energy generators, an evaluation method for TOV of MRESS is derived. Through analyzing the relationship between TOV of the system and short-circuit ratio, the temporary overvoltage short-circuit ratio (TOVSCR) of MRESS and its application method are proposed. Simulation results show that the proposed method can effectively evaluate the TOV risk and safety margin of the MRESS.
Peer Review Status:
Awaiting Review
Subjects: Dynamic and Electric Engineering >> Electrical Engineering Subjects: Mathematics >> Control and Optimization. submitted time 2022-08-07
Xiaodong Zheng
Baorong Zhou
Xiuli Wang
Bo Zeng
Jizhong Zhu
Haoyong Chen
Peizheng Xuan
Waisheng Zheng
Abstract： Quick-start generation units are critical devices and flexible resources to ensure a high penetration level of renewable energy in power systems. By considering the wind uncertainty, and both binary and continuous decisions of quick-start units within the intraday dispatch, we develop a Wasserstein-metric-based distributionally robust optimization model for the day-ahead network-constrained unit commitment (NCUC) problem with mixed integer recourse. We propose two feasible frameworks for solving the optimization problem. One approximates the continuous support of random wind power with finitely many events, the other leverages the extremal distributions instead. Both solution frameworks rely on the classic nested column-and-constraint generation (C&CG) method. It is shown that due to the sparsity of L1-norm Wasserstein metric, the continuous support of wind power generation could be represented by a discrete one with a small number of events, and the extremal distributions rendered are sparse as well. With this reduction, the distributionally robust NCUC model with complicated mixed-integer recourse problems can be efficiently handled by both solution frameworks. Numerical studies are carried out, demonstrating that the model considering quick-start generation units ensures unit commitment (UC) schedules to be more robust and cost effective, and the distributionally robust optimization method captures the wind uncertainty well in terms of out-of-sample tests.
Hits
Hits
Downloads
Comment
YES