Multi-level optimization approach for directly coupled photovoltaic-electrolyser system

In this study, directly coupled photovoltaic-electrolyser system is designed and optimized and a new method for optimization is given. The accurate electrical models of advanced alkaline electrolyser, photovoltaic system, and hydrogen storage tank are simulated using Matlab. The system is investigated for a day using actual meteorological data of Miami, FL. The purpose of the optimization, which has been performed using genetic algorithm, is to produce maximum hydrogen, minimum excess power, and minimum energy transfer loss. In each iteration of the optimization, due to crucial role of temperature in overall performance of the system, the average operating temperature is optimized using genetic algorithm. The system is optimized in a way that the operating condition is as close as possible to the maximum power point of the photovoltaic array. The operation of the system is discussed in 24 h period and working hours to make the system comparable to other studies with different power sources. The result of the analysis shows that optimal system for a 10 kW electrolyser can produce the average hydrogen of 0.0151 mol/s when the system is operating with 2.2% power loss and 4.7% power transfer loss.