A COMPARISON OF PROBABILISTIC-MONTE CARLO AND FUZZY-MONTE CARLO SIMULATION APPROACHES FOR DYNAMIC FAULT TREE: CASE OF RENEWABLE POWER SYSTEMS

Conventional Fault Tree Analysis (FTA) suffers from a variety of shortcomings which must be considered in critical analysis. The main disadvantage of FTA is its inability to model the dynamic failure behaviors of the components. Accordingly, Dynamic Fault Tree Analysis (DFTA) has been proposed to overcome such limitation. In this study, first, Monte Carlo simulation (MSC) approach is used to handle internal calculations of dynamic gates. The second main weakness of common FTA is about handling the different types of uncertainties. Hence, in the second step of this study, a combined of fuzzy numbers and MCS has been proposed to overcome the limitation of FTA in dealing with uncertainties. The main purpose of this paper is a comparative study on differences between MCS and Fuzzy-Monte Carlo simulation (FMCS) approaches for solving DFTA of a typical mechanical system. From available literatures, our proposed approaches have been demonstrated on different renewable energy systems, as case studies, and results are discussed. A comparison between MCS and FMCS shows that the results of FMCS method are reasonable and more realistic. Finally, in the last section, conclusions and some of the future wok are proposed.