Monte Carlo Simulation for Reliability Assessment of Electrical Power Generation Systems with Renewable Resources

In face of the increasing adoption of renewable sources like solar and wind, traditional reliability assessments need revision. Conventional methodologies, designed for predictable and controllable energy sources, fall short in addressing the uncertainty of renewables. This study aims to develop a methodology for assessing the reliability of Generation Systems (GS), focusing on renewable integration and analyzing a real Brazilian system. The innovation lies in incorporating probabilistic models to handle the variability and unpredictability of renewable resources, resulting in robust reliability analysis. The proposed methodology employs sequential and synchronous Monte Carlo simulations to calculate reliability indices, such as Loss of Load Expectation, Loss of Load Probability and Expected Energy Not Served. Validation was done on a real system from Minas Gerais. Results show that including renewables can significantly improve reliability indices. Thus, advanced reliability assessment methodologies are vital for addressing renewable uncertainties and enhancing system robustness.