An Improved Particle Swarm Optimization Algorithm-Based MPPT Method for Distributed Photovoltaic Hydrogen Production Systems

In order to cope with the increase in carbon emissions caused by the excessive use of fossil energy, the world's energy structure needs to be adjusted. Distributed photovoltaic (PV) hydrogen production system, as an integrated energy system, is an important pathway to the zero-carbon goal. But distributed PV is prone to face the shading situation, while the PV module power output curve will show the phenomenon of multiple peaks. The traditional maximum power tracking methods are prone to fall into the local optimal situation, and the intelligent tracking methods are inherently more complex. The hydrogen production electrolyzer puts forward the requirement of stability on the output power of the PV power supply. Existing research focuses on the maximum power tracking of PV system, or the control of electrolyzer, lacking the coupled modeling control research of distributed PV hydrogen production system. In order to fill the gap of the existing research, this paper proposes a composite algorithm which combines the Improved Particle Swarm Algorithm (IPSO) with the Improved Perturbation Observation (IP&O) method. The initial population and termination conditions of the particle swarm search method (PSO) are improved to enhance the convergence speed of the algorithm and reduce the oscillations during the convergence process of the algorithm, and the IP&O method is utilized to provide stable inputs for the electrolytic tanks. The performance of the algorithm is verified through the comparative experiments with other algorithms.