Sequential Monte Carlo Reliability Analysis for Economical High-Renewable Microgrids

Microgrid (MG) designs need to achieve a balance between the economic and reliability objectives. Residential and commercial consumers currently express interest in maximizing renewable resources in their generation mix. However, techno-economic analyses are required to insure the viability of microgrids with high levels of renewables. This paper proposes a novel approach to estimate composite power system reliability based on historical failure data and statistical analyses. A time series analysis is performed using sequential Monte Carlo simulation (SMCS) to sample components' failure and healthy states during a MG life cycle. Methodology is applied to a real-life MG designed to serve a small commercial load. Alternative high-renewable penetration systems, between 80 and 100%, are analyzed. Results show the expected economical-reliability tradeoff associated with high renewable percentages.