Fault Tree Reliability Analysis of a Micro-grid.pdfVIP

Abstract— In this paper, the traditional Fault Tree Analysis (FTA) method combined with Monte Carlo simulations (MCSs) is introduced to a real micro-gird with significant clean energy penetration. Importance of different components in the micro- grid is first found using the traditional FTA but cannot show a clear illustration of the system’s reliability with respect to time. Using the proposed fault-tree-MCS (FT-MCS) method, a simulation program can be established with random sampling time. In this process, the contribution of each part to the whole system reliability can be clearly shown with varying time. A more accurate Mean Time to Failure (MTTF) can thus be achieved using the FT-MCS. FT-MCS is shown to combine the benefits of fault tree component hierarchy for fault propagation, as well as fault occurrence over time. Keywords —Fault Tree Analysis, Micro-grid, Monte Carlo Simulation, Reliability I. INTRODUCTION AULT Tree Analysis (FTA) is a top-down deductive failure analysis approach commonly used to determine root causes of failures where failures and their modes are connected with logic gates and binary numbers [1]. It is widely used for system reliability modeling and analysis. Traditional FTA uses an analytical approach that is fast and computationally efficient. For example, the structure importance coefficient which is the main reliability metric in FTA, can be calculated based on cut sets of the fault tree. Other metrics such as the failure probability of different paths in the tree can be determined based on failure probability distributions or failure rates taken from the literature. Main reliability analysis methods in FTA include direct calculation of structure importance coefficients [2, 3] and fuzzy number fault trees [4-6]. A structure importance coefficient is the degree of importance of an event and relates to the component’s location and importance in the physical system, not to the component’s failure probabi