Distributionally Robust Resilience Assessment of Power Systems with Offshore Wind Farms

More and more offshore wind farms (OWFs) are integrated into the power system to achieve sustainable energy development. Extreme events such as hurricanes damage transmission lines and affect OWFs power output. Considering the uncertain nature of hurricane evaluation stages, a novel jointed data and model-driven distributionally robust ambiguity set is formulated to quantify the impacts of hurricanes on power systems with OWFs. A Monte-Carlo simulation based assessment method is adopted to assess the resilience of power systems under nominal PDFs. The distributionally robust conditional value at risk (DRO-CVaR) is proposed to quantify the resilience of power systems with OWFs under total variation distance-based ambiguity density function. Simulations are performed on a modified IEEE RTS-24 system under the Kenta hurricane. The results indicate that the resilience of power systems towards hurricanes under distributionally robust ambiguities can be captured by nodal reliability level.