Equitable Networked Microgrid Topology Reconfiguration for Wildfire Risk Mitigation

TL;DR

This work introduces a rolling-horizon, equity-aware topology reconfiguration method for networked microgrids to mitigate wildfire risk during PSPS events. It integrates power-flow, storage, and inverter constraints with risk-based and fairness constraints, guiding dynamic reconfiguration to minimize load shedding while protecting vulnerable communities. The approach is validated on a modified IEEE 13-bus feeder and the large-scale Smart-DS system, showing improved fairness in shutoffs and scalable performance. The framework enables more resilient and just distribution-grid operations under extreme wildfire conditions, with potential extensions to uncertainty and broader equity dimensions.

Abstract

The increasing number of wildfires in recent years consistently challenges the safe and reliable operations of power systems. To prevent power lines and other electrical components from causing wildfires under extreme conditions, electric utilities often deploy public safety power shutoffs (PSPS) to mitigate the wildfire risks therein. Although PSPS are effective countermeasures against wildfires, uncoordinated strategies can cause disruptions in electricity supply and even lead to cascading failures. Meanwhile, it is important to consider mitigating biased decisions on different communities and populations during the implementation of shutoff actions. In this work, we primarily focus on the dynamic reconfiguration problem of networked microgrids with distributed energy resources. In particular, we formulate a rolling horizon optimization problem allowing for flexible network reconfiguration at each time interval to mitigate wildfire risks. To promote equity and fairness during the span of shutoffs, we further enforce a range of constraints associated with load shedding to discourage disproportionate impact on individual load blocks. Numerical studies on a modified IEEE 13-bus system and a larger-sized Smart-DS system demonstrate the performance of the proposed algorithm towards more equitable power shutoff operations.

Figures (6)

• Figure 1: The modified test case from IEEE 13 bus system.
• Figure 2: The wildfire risk $r_{\kappa,t}$ values for different load blocks.
• Figure 3: The network topology of the 13-bus test case after reconfiguration at time (a) $t = 1$; (b) $t = 2$; and (c) $t = 3$.
• Figure 4: Comparison of computation time under different $\epsilon$ values.
• Figure 5: Comparison of load shedding under different $\epsilon$ values.