Chance constraint based risk-aware optimal power flow for cascading failure prevention
Date of Original Version
Once part or whole of the power system is exposed to some dangerous situations, e.g., malicious terrorist attacks or extreme weather conditions, the potential cascading failure is a severe threat to the power system. However, some feasible prevention control strategies can be used to enhance the system robust to cope with the impact of cascading failure. This paper proposed a chance constraint based optimal power flow model considering the impact of cascading failure. Compared to the conventional optimal power flow model, the proposed one can obtain the optimal generation profile that satisfies the chance constraint on the risk level of cascading failure. Power redispatch that is implemented according to the obtained generation profile can be seen as a prevention strategy, which can reduce the threat of cascading failure to an acceptable level. PSO algorithm and Monte Carlo method were used to search for the optimal solution. Case studies on the IEEE 39-bus system illustrate the effectiveness of the proposed model.
Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference
Luo, Chao, Jun Yang, Yufei Tang, Haibo He, and Mingsong Liu. "Chance constraint based risk-aware optimal power flow for cascading failure prevention." Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference 2016-July, (2016). doi:10.1109/TDC.2016.7520014.