Reliability Assessment of Power System Microgrid Using Fault Tree Analysis: Qualitative and Quantitative Analysis

Renewable energy sources account for approximately one-quarter of the total electric power generating capacity in the United States. These sources increase system complexity, with potential negative impacts caused by their inherent variability. A microgrid, a decentralized local grid, offers an excellent solution for integrating these sources into the system’s generation mix in a cost-effective and efficient manner. This paper presents a comprehensive fault tree analysis for the reliability assessment of microgrids, ensuring their safe operation. In this work, fault tree analysis of a microgrid in grid-tied mode with solar, wind, and battery energy storage systems is performed, and the results are reported. The analyses and calculations are performed using the Relyence software suite. The fault tree analysis was performed using various calculation methods, including exact (conventional fault tree analysis), simulation (Monte Carlo simulation), cut-set summation, Esary–Proschan, and cross-product. Once these analyses were completed, the results were compared with the ‘exact’ method as the base case. Critical risk measures, such as unavailability, conditional failure intensity, failure frequency, mean unavailability, number of failures, and minimal cut-sets, were documented and compared. Importance measures, such as marginal or Birnbaum, criticality, diagnostic, risk achievement, and risk reduction worth, were also computed and tabulated. Details of all cut-sets and the probability of failure are presented. The calculated importance measures would help microgrid operators focus on events that yield the greatest system improvements and maintain an acceptable range of risk levels to ensure safe operation and improved system reliability.