“…Both modes need to ensure the reliability of the output energy with little to no disruption to the connected load during the operation hours [12]. Furthermore, the modes also need to ensure the battery storages can perform better and improve the utilization of renewable energy systems [9,[13][14][15]. Looking at the importance of battery storage charging -discharging, methods or mechanisms such as the Adaptive Neuro-Fuzzy Inference System (ANFIS) [6,16,17], backtracking search algorithm [10,18,19], non-simultaneous charging and discharging [20], genetic algorithm [4,21], particle swarm optimized fuzzy controller [22][23][24][25][26][27], model predictive control [28][29][30][31][32], dynamic optimal power flow [33][34][35][36], and grey model and genetic algorithms [37] are commonly used to perform the battery storage charging and discharging.…”