Electrical power generation by an optimised autonomous PV/wind/tidal/battery system

The main contributions of this study are to (i) incorporate tidal power into a hybrid PV/wind/battery renewable energy system and (ii) introduce a new metaheuristic technique named crow search algorithm (CSA) for optimisation of the PV/wind/tidal/battery system. For this aim, power equations of the different components are introduced and an objective function is defined based on the economic analysis of the system. The proposed CSA is then used to optimally size the PV/wind/tidal/battery system. On the case study, simulation results show that using tidal energy decreases the total cost of the system. Moreover, the proposed CSA produces better results in comparison with two well-known metaheuristic methods, namely, particle swarm optimisation and genetic algorithm in terms of accuracy and run time.