Time-Decoupling Layered Optimization for Energy and Transportation Systems under Dynamic Hydrogen Pricing

Hui Guo, Dandan Gong, Lijun Zhang, Wenke Mo, Feng Ding and Fei Wang
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Hui Guo: School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200444, China
Dandan Gong: School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200444, China
Lijun Zhang: Instituto Superior Técnico, University of Lisbon, 999022 Lisbon, Portugal
Wenke Mo: Shanghai Marine Equipment Research Institute, Shanghai 200031, China
Feng Ding: Shanghai Marine Equipment Research Institute, Shanghai 200031, China
Fei Wang: School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200444, China

Energies, 2022, vol. 15, issue 15, 1-18

Abstract: The growing popularity of renewable energy and hydrogen-powered vehicles (HVs) will facilitate the coordinated optimization of energy and transportation systems for economic and environmental benefits. However, little research attention has been paid to dynamic hydrogen pricing and its impact on the optimal performance of energy and transportation systems. To reduce the dependency on centralized controllers and protect information privacy, a time-decoupling layered optimization strategy is put forward to realize the low-carbon and economic operation of energy and transportation systems under dynamic hydrogen pricing. First, a dynamic hydrogen pricing mechanism was formulated on the basis of the share of renewable power in the energy supply and introduced into the optimization of distributed energy stations (DESs), which will promote hydrogen production using renewable power and minimize the DES construction and operation cost. On the basis of the dynamic hydrogen price optimized by DESs and the traffic conditions on roads, the raised user-centric routing optimization method can select a minimum cost route for HVs to purchase fuels from a DES with low-cost and/or low-carbon hydrogen. Finally, the effectiveness of the proposed optimization strategy was verified by simulations.

Keywords: layered optimization; renewable energy; hydrogen-powered vehicle; dynamic hydrogen pricing; routing optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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