Two-level model predictive control energy management strategy for hybrid power ships with hybrid energy storage system

被引:36
|
作者
Zhang, Yijie [1 ]
Xue, Qimeng [1 ]
Gao, Diju [1 ]
Shi, Weifeng [2 ]
Yu, Wanneng [3 ]
机构
[1] Shanghai Maritime Univ, Key Lab Transport Ind Marine Technol & Control Eng, Shanghai 201306, Peoples R China
[2] Shanghai Maritime Univ, Logist Engn Coll, Shanghai 201306, Peoples R China
[3] Fujian Prov Key Lab Ship & Ocean Engn, Xiamen 361021, Fujian, Peoples R China
关键词
Hybrid power ship; Model predictive control; Hybrid energy storage system; Energy management strategy; FRAMEWORK;
D O I
10.1016/j.est.2022.104763
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Compared with the load power characteristics of ground power systems, the intermittent and random fluctuation of ship load power demand brings challenges to the energy management system of ship power systems. To achieve fuel economy and solve the problem of power fluctuation, the hybrid energy storage system (HESS) composed of the battery pack and ultra-capacitor is applied to the diesel-electric hybrid ship. A two-level model predictive control (MPC) strategy consisting of two optimization stages is proposed. The first stage aims to determine the power distribution solution of the diesel generator and battery at a large time-scale. In the second stage, the operation strategy of the ultracapacitor is determined at a small time-scale based on the power dis-tribution solution of the first stage. The conventional MPC-based strategy and global optimization strategy based on dynamic programming (DP) are compared with the proposed strategy. The simulation results show that the proposed strategy has better fuel saving ability, and realizes the clear power frequency division between the supercapacitor and battery. In addition, the proposed strategy can also approach the performance of global optimization.
引用
收藏
页数:10
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