An Energy Optimization Strategy for Hybrid Power Ships under Load Uncertainty Based on Load Power Prediction and Improved NSGA-II Algorithm

Abstract

In this paper, a hybrid ship powered by diesel generator sets and power batteries in series is considered. By analyzing the characteristics of hybrid ship cycle operating conditions, the load power of the hybrid ship under load uncertainty is firstly predicted. Then, considering the economy, emissions and continuous navigation time (endurance) of the hybrid ship, an energy optimization strategy based on the predicted load power is proposed to achieve the goal of minimum fuel consumption, minimum emissions and maximum endurance of ship operation. The experimental results show that, compared with the fuzzy logic rules based strategy, the fuel economy of the ship is increased by 9.6% and the ship’s endurance is increased by 24% for the proposed strategy.