New advances in integrating fuzzy data in Monte Carlo simulation to evaluate reliability indices of composite power systems

In this paper, several concepts related to the application of Monte Carlo simulation to evaluate the reliability indices of composite power systems are reviewed. In the sequence of previous papers, one integrates in the Monte Carlo simulation a DC fuzzy optimal power flow model to cope with uncertainties in peak loads. This general framework is now enhanced as one can specify fuzzy load duration curves, uncertainties in repair and failure rates and can adopt either nonchronological or chronological sampling strategies. This package can thus be used to evaluate the impact in the expected values of power and energy not supplied of uncertainties affecting several variables and parameters