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Article Dans Une Revue Energies Année : 2018

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

Diju Gao
  • Fonction : Auteur correspondant
Tianzhen Wang

Résumé

In this paper, a hybrid ship powered by diesel generator sets and power batteries inseries 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 theeconomy, emissions and continuous navigation time (endurance) of the hybrid ship, an energyoptimization strategy based on the predicted load power is proposed to achieve the goal of minimumfuel consumption, minimum emissions and maximum endurance of ship operation. The experimentalresults show that, compared with the fuzzy logic rules based strategy, the fuel economy of the ship isincreased by 9.6% and the ship’s endurance is increased by 24% for the proposed strategy.
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Dates et versions

hal-01918942 , version 1 (12-07-2019)

Identifiants

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Diju Gao, Xuyang Wang, Tianzhen Wang, Yide Wang, Xiaobin Xu. An Energy Optimization Strategy for Hybrid Power Ships under Load Uncertainty Based on Load Power Prediction and Improved NSGA-II Algorithm. Energies, 2018, 11 (7), pp.1699. ⟨10.3390/en11071699⟩. ⟨hal-01918942⟩
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