Value of considering extreme weather resilience in grid capacity expansion planning

Extreme weather events have a significant impact on the operation of the power grid. Due to this impact, lines and generators go out of service, causing damage to grid resources, blocking service to demand locations, and therefore hindering the power flow. Proactive capacity expansion might provide the much-needed slack that helps the grid maximize the power demand it is able to satisfy during these events. Therefore, considering the resilience of the grid and performance during extreme weather events in capacity expansion might be part of a long-term resilience solution. Towards that end, we study a resilience-informed capacity expansion framework. The framework has three steps: a two-stage stochastic programming model for the optimal expansion of generators and lines in the power grid up to a target year, a “scheduling†model for developing a comprehensive expansion plan over time, and an evaluation model to measure performance of the expanded grid under various extreme weather scenarios. The goal of the framework is to optimally make capacity expansion investments to satisfy the demand growth and increase resilience simultaneously by minimizing the load shed across a variety of extreme weather scenarios. We present computational results on a problem instance representative of the Texas grid using hurricane-induced flood events as extreme weather scenarios under various combinations of plausible demand growth and reserve margin parameters. We compare the results of the resilience-informed framework with those of a more conventional expansion planning approach where extreme weather performance is not taken into account to demonstrate the value of considering resilience in making capacity expansion decisions.