Cut-set and Stability Constrained Optimal Power Flow for Resilient Operation During Wildfires

Resilient operation of the power system during ongoing wildfires is challenging because of the uncertain ways in which the fires impact the electric power infrastructure (multiple arc-faults, complete melt-down). To address this challenge, we propose a novel cut-set and stability-constrained optimal power flow (OPF) that quickly mitigates both static and dynamic insecurities as wildfires progress through a region. First, a Feasibility Test (FT) algorithm that quickly desaturates overloaded cut-sets to prevent cascading line outages is integrated with the OPF problem. Then, the resulting formulation is combined with a data-driven transient stability analyzer that predicts the correction factors for eliminating dynamic insecurities. The proposed model considers the possibility of generation rescheduling as well as load shed. The results obtained using the IEEE 118-bus system indicate that the proposed approach alleviates vulnerability of the system to wildfires while minimizing operational cost

Estimating Relevant Portion of Stability Region using Lyapunov Approach and Sum of Squares

Traditional Lyapunov based transient stability assessment approaches focus on identifying the stability region (SR) of the equilibrium point under study. When trying to estimate this region using Lyapunov functions, the shape of the final estimate is often limited by the degree of the function chosen, a limitation that results in conservativeness in the estimate of the SR. More conservative the estimate is in a particular region of state space, smaller is the estimate of the critical clearing time for disturbances that drive the system towards that region. In order to reduce this conservativeness, we propose a methodology that uses the disturbance trajectory data to skew the shape of the final Lyapunov based SR estimate. We exploit the advances made in the theory of sum of squares decomposition to algorithmically estimate this region. The effectiveness of this technique is demonstrated on a power systems classical model.Comment: Under review as a conference paper at IEEE PESGM 201