Optimization control method of dual channel hydrogen production system for multi-power scenarios based on MOPSO-EEMD

In response to the adverse effects of the volatility and randomness of wind and photovoltaic resources on the stable and efficient operation of hydrogen production systems, an optimization control method for multi-power scenario dual channel hydrogen production systems based on multi-objective particle swarm optimization (MOPSO) and ensemble empirical mode decomposition (EEMD) is proposed in this paper. A hybrid hydrogen production system consisting of alkaline electrolysis cells, proton exchange membrane electrolysis cells (PEM), and fuel cells is constructed based on the differences in adaptability of different hydrogen production equipment to fluctuating inputs, the EEMD is used to decompose the initial wind and photovoltaic output power, and the initial power of electrolysis cells is allocated by Petri net-based start stop rule correction method. An optimization control model of dual channel electrolysis cells based on multi-objective optimization is established with the goals of wind and photovoltaic energy conversion efficiency and unit hydrogen production cost, and the power distribution between alkaline electrolysis cells and PEM electrolysis cells is achieved by optimizing the intrinsic mode component reconstruction using the MOPSO algorithm. The effectiveness of the method proposed in this paper is verified through simulation examples of actual operating data at a certain wind and photovoltaic power station. The analysis results of the example show that compared to single channel hydrogen production, the optimized control of the dual channel hydrogen production system has achieved significant improvements in economy and energy utilization efficiency.