Comparison of particle swarm and genetic algorithm based design algorithms for PV-hybrid systems with battery and hydrogen storage path

The paper describes a new optimizing design concept for autonomous power supply systems employing an enhanced particle swarm algorithm taking into account both component sizing and energy management parameters. The structure of the overall optimization problem is investigated showing high complexity and nonlinearity particularly for switching energy management strategies. The specific features of the enhanced particle swarm optimization algorithm are discussed. The new optimizing design concept is investigated for two application examples, a private household and a small agricultural holding. The performance of the enhanced particle swarm algorithm is compared to two reference algorithms, a standard particle swarm and a genetic algorithm. The enhanced particle swarm algorithm shows the highest accuracy and fastest convergence speed for both applications and for both energy management strategies.