A novel optimal dispatch strategy for hybrid energy ship power system based on the improved NSGA-II algorithm.

As the most promising future generation green ship, hybrid energy ship power systems (HESPS) have gradually attracted attention. However, the integration of new energy including wind energy and solar energy, raises key challenges in designing a suit optimal dispatch for HESPS under different navigation conditions. Based on this, an optimal dispatch strategy using the improved Non-dominated Sorting Genetic (NSGA-II) algorithm is proposed. Firstly, an integrated HESPS model consisting of diesel power generation system, energy storage system (ESS), wind power generation system (WPGS) and photovoltaic power generation system is established. Based on this, a multi-objective optimization strategy is proposed to reduce the cost and greenhouse gas emissions. Through the design of crossover operator and mutation operator, an improved NSGA-II is developed to find optimal solutions. Finally, three cases are presented to test the performance of proposed optimal dispatch strategy. Compared with traditional NSGA-II and multi-objective particle swarm optimization (MOPSO), the indicator of Hypervolume, Proportion of independent solutions, Generational Distance (GD) and Inverted Generational Distance can be improved at least 0.39%, 0.18%, 1.85% and 15.87%. At the same time, the corresponding cost and energy efficiency operational index (EEOI) of HESPS can be reduced by 13.17% and 17.53%. • Hybrid energy ship model including DGs, ESS, WPGS, PV etc., is explored. • A novel optimal dispatch strategy using the improved NSGA-II is proposed. • Compared with existing methods, optimization performance can be improved. • EEOI and reduce greenhouse gas emissions can be reduced by 13.17% and 17.53%. [ABSTRACT FROM AUTHOR]