A Cloud Model-Based Optimal Combined Weighting Framework for the Comprehensive Reliability Evaluation of Power Systems with High Penetration of Renewable Energies

Reliability has long been a critical attribute of power systems that cannot be ignored. Numerous blackout events have highlighted the increasing risk of outages in power systems due to the prominence of high-proportion power electronics and renewable energy utilization. Traditional reliability assessment methods, which typically take dozens of hours to assess the adequacy of steady-state conditions, cannot reflect the real-time reliability performance of the system. Moreover, the weakness identification methods can only quantify the impact of component outages while ignoring other important operational factors. To address these issues, this paper constructs a three-hierarchy reliability evaluation index system (REIS) for power systems, consisting of the comprehensive reliability evaluation index (CREI) as the top hierarchy, four primary indices in the middle, and lots of subjective and objective indices on the bottom. To quantify the performance of different calculation methods for these indices, a combined weighting framework is proposed. Finally, the REIS level is evaluated according to the Wasserstein distances between the CREI cloud model and standard cloud models. In the case study, the proposed method is verified through its application to the power grids of two cities in a province in southern China, demonstrating its practicality and effectiveness.