Stochastic Resource Allocation for Electricity Distribution Network Resilience

Abstract

In recent years, it has become crucial to improve the resilience of electricity distribution networks (DNs) against storm-induced failures. Microgrids enabled by Distributed Energy Resources (DERs) can significantly help speed up reenergization of loads, particularly in the complete absence of bulk power supply. We describe an integrated approach which considers a pre-storm DER allocation problem under the uncertainty of failure scenarios as well as a post-storm dispatch problem in microgrids during the multi-period repair of the failed components. This problem is computationally challenging because the number of scenarios (resp. binary variables) increases exponentially (resp. quadratically) in the network size. Our overall solution approach for solving the resulting two-stage mixed-integer linear program (MILP) involves implementing the sample average approximation (SAA) method and Benders Decomposition. Additionally, we implement a greedy approach to reduce the computational time requirements of the poststorm repair scheduling and dispatch problem. The optimality of the resulting solution is evaluated on a modified IEEE 36node network.

Extensive-form Game-Based Pre-Disaster Resilience Planning Considering Post-Disaster Restoration Decisions

“…A pre-disaster allocation scheme of repair crew and power supply resources is proposed in (Wallnerström and Hilber, 2013) considering the cost to minimize the power grid vulnerability index. Considering uncertainties of failure scenarios, (Chang et al, 2020), established a two-stage model for prestorm DER allocation problem. Its efficiency is guaranteed by implementing sample average approximation method and Benders decomposition.…”