Efficient Methods to Calculate the Reliability of Energy Systems with Correlated Renewable Sources

Abstract

This article proposes methods that use nonsequential Monte Carlo Simulation (MCS) to calculate reliability indices of power systems with correlated energy sources. The methods apply Principal Correlated Analysis (PCA), covariance matrix, random variable transformation and correlation mapping. Good results were found in cases with linear correlations and high failure state frequency. The processing time was consistent with that observed in classical nonsequential Monte Carlo simulation, and with PCA, it was possible to reduce the dimensionality of the system.