Battery management system in isolated microgrids considering forecast uncertainty

Abstract

Microgrids are gaining a significant interest as a promising solution to handle several electricity-related issues worldwide. Isolated Microgrids as one of the most applied topologies in the emergency power supplying systems, essentially incorporate battery storage system (BSS), acting as a stabilizing agent by balancing the unmet power for the system. Moreover, BSS is playing a great role in the context of energy cost minimizing of the system. This work proposes an adaptive operation policy for BSS in an isolated microgrid incorporating conventional generation (e.g. Diesel Generator) and Renewable resources (e.g. PV solar array) in addition to BSS, based on the driven forecast. Yet, it handles the uncertain prediction of both renewable generation and load profile. More precisely, an offline optimal policy of charging and discharging of BSS is firstly derived assuming a perfect prediction and the algorithm then responds instantaneously to act upon the actual changes of the given forecast. The simulation results show a significant reduction of the total operation cost, even in the worst case scenario, when compared with the blind method which does not employ the prediction.