Energy Management of Hybrid Power Ship System Using Adaptive Moth Flame Optimization Based on Multi-Populations
Lei Xu, Xiaoyuan Luo, Yintang Wen, Tao Wu, Xinyu Wang, Xinping Guan
Abstract
With the accelerating of electrification of ship power system, it enables a more efficient and flexible operation to alleviate the pressure on environment pollution and energy consumption. Hitherto, many existing literatures have achieved the optimal electric energy management on board, with the application of diesel generator and electric energy storage, while the thermal energy scheduling has been barely studied. In this paper, the electric energy and thermal energy scheduling are studied simultaneously, thus expanding the ship power system into hybrid power ship system (HPSS). Considering the total operating cost and Greenhouse Gases (GHG) emissions, the energy scheduling optimization problem is defined. To improve the quality of solution, an adaptive moth flame optimization based on multi-populations (AMFOMP) is proposed. Specifically, moth sorting strategy based on logistic mapping, nonlinear flames number update mechanism and modified update formula of moth are carried out to improve the exploration and exploitation ability in iterations. Moreover, modified opposition-based learning and population diversity strategy are implemented to prevent algorithm from stagnation. AMFOMP is carried out into electric and thermal energy scheduling and the simulation results show the economic and environmental benefits of the proposed HPSS.