Optimal selection and analysis of microgrid energy system using Markov process

Abstract

This study investigated the reliability of a microgrid (MG) energy system using the Markov process reliability method. Twenty possible MG configurations based on photovoltaic (PV), wind turbine generator (WTG), biomass generator (BMG), battery bank (BB), diesel generator (DG) and an electric vehicle (EVs) have been considered. This study also selects an optimal configuration based on reliability indices (failure rate, repair time, unavailability, expected energy not supplied (EENS) and loss of load probability (LOLP)), annually load demand, availability of the system and its components. The results show that the hybrid PV/WTG/BMG/BB/EVs/DG microgrid system has the lowest system failure rate (0.01012 /year), repair time (1.1858 hrs), unavailability (0.0120 hrs/year), EENS (4.5 kWh/year) and LOLP (1.36986E-06 /year). This MG configuration has an availability of 99%. The PV array (97.55%) and the changeover switch (99.5%) are the parts of the MG system that are the most reliable. The least stable elements of an MG system are battery (63.64%), diesel generator (80%) and biomass generator (83.89%). PV (62%) and WTG (28% of total) are the main contributors to electricity generation, with the battery, electric vehicles, and diesel generator acting as backup sources. Under different weather and load conditions, the hybrid PV/WTG/BMG/EVs/BB/DG microgrid was found to be a reliable and efficient system for remote areas. This research carries a significant impact for policymakers, government, energy planners, and researchers working on stand-alone microgrid systems as it provides valuable insights into optimizing system configuration for reliability and efficiency.