Risk Assessment of Wind-PV Integrated Systems Under Rainstorm Conditions Based on Improved Monte Carlo Simulation Sampling

This study develops a risk assessment model for power systems under extreme rainfall conditions, addressing the gap in traditional methods that overlook the photovoltaic (PV) performance in low-light scenarios during rainstorms. By combining Latin Hypercube Sampling (LHS) with conventional Monte Carlo simulation techniques, the proposed approach accelerates the risk assessment process while improving its accuracy. Risk evaluation metrics are systematically defined, and an optimal power flow (OPF) model is used to quantify load-shedding requirements. The methodology is validated through simulations on the IEEE 33-bus system, with comparative analysis against baseline Monte Carlo simulations demonstrating the superior computational efficiency and feasibility of the proposed framework. Moreover, the study provides valuable insights into risk quantification for power systems affected by rainstorm conditions.