The impact of using Particle Swarm Optimisation on the operational characteristics of a stand-alone hydrogen system with on-site water production

In a previous paper, we analysed the impact of renewable energy intermittency on the operational characteristics of hydrogen energy systems with pre-set Power Management Strategies not subject to optimisation. The research presented in this follow-up paper extends that earlier work and demonstrates the validity of applying Particle Swarm Optimisation (PSO) to size and optimise hydrogen systems. Specifically, PSO is used to iteratively converge on the (short-term) battery capacity (Ah) and hydrogen storage (L) in addition to defining the switching parameters which a Power Management Strategy (PMS) uses. The PSO algorithm is guided by three operational objective functions and conducted using MATLAB/Simulink. Simulations also incorporate laboratory resolved device characteristics. s are benchmarked against earlier deployed methods and show improvements with a PSO optimised PMS depend on system scale, with greater relative benefits arising at smaller scales. The choice of PSO acceleration parameters also affects the time to reach an optimal solution.