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Open AccessArticle

Game-Based Energy Management Method for Hybrid RTG Cranes

1
Key Laboratory of Transport Industry of Marine Technology and Control Engineering, Shanghai Maritime University, Shanghai 201306, China
2
School of Computing and Engineering, University of Huddersfield, Huddersfield HD1 3DH, UK
*
Author to whom correspondence should be addressed.
Energies 2019, 12(18), 3589; https://doi.org/10.3390/en12183589
Received: 15 August 2019 / Revised: 12 September 2019 / Accepted: 13 September 2019 / Published: 19 September 2019
In order to improve the energy efficiency and economic effect of conventional diesel-powered rubber-tired gantry (RTG) cranes in container terminals, various hybrid RTG cranes were studied. However, these current hybrid RTG cranes have several disadvantages, such as high initial investment cost and poor versatility of energy management methods. In this paper, a hybrid RTG crane consisting of a small-sized diesel generator (DG), a ternary material lithium battery, and a supercapacitor (SC) is studied, and a hybrid RTG crane energy management method based on game theory is proposed. The DG, lithium battery, and SC are modeled as three independent agents to participate in the game, and a multi-agent system (MAS) is established. During the RTG crane work process, agents achieve a coordinated and stable working state through the game, i.e., the Nash equilibrium. Three typical crane operation scenarios, the rated load, continuous work, and intermittent work, are simulated and studied. According to the results, combinations of the three devices can meet the power demand and system performance. The power of the DG in the hybrid system is small (only 20 kW), reducing fuel consumption and overall emissions during RTG crane operation. View Full-Text
Keywords: energy management methods; hybrid RTG crane; game theory; lithium-ion battery; supercapacitor; diesel generator energy management methods; hybrid RTG crane; game theory; lithium-ion battery; supercapacitor; diesel generator
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Chen, D.; Niu, W.; Gu, W.; Schofield, N. Game-Based Energy Management Method for Hybrid RTG Cranes. Energies 2019, 12, 3589.

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