A Probabilistic and Cost-based Decision Strategy for Power Grid Resilience using Ensemble Forecasting

Preventive actions such as intentional islanding are a promising way of effectively improving power grid resilience and mitigating the propagation of cascading faults caused by extreme weather events. However, the stochastic nature of weather and uncertainty in weather forecasts make the decision on whether to apply a preventive action difficult. This paper presents a novel decision strategy that utilizes the probabilities provided by ensemble forecasting to decide whether to apply a preventive action prior to an extreme event and to identify the most cost-effective preventive action. This probability-based strategy is compared to traditional decision strategies that either only consider the most likely weather prediction or the most severe. The application of the proposed probability-based decision strategy to the German transmission network in combination with preventive islanding shows significant cost reductions and underlines the benefits of ensemble forecasting to boost power grid resilience.