LAPSE:2023.10820
Published Article
LAPSE:2023.10820
Time-Decoupling Layered Optimization for Energy and Transportation Systems under Dynamic Hydrogen Pricing
Hui Guo, Dandan Gong, Lijun Zhang, Wenke Mo, Feng Ding, Fei Wang
February 27, 2023
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
dynamic hydrogen pricing, hydrogen-powered vehicle, layered optimization, Renewable and Sustainable Energy, routing optimization
Suggested Citation
Guo H, Gong D, Zhang L, Mo W, Ding F, Wang F. Time-Decoupling Layered Optimization for Energy and Transportation Systems under Dynamic Hydrogen Pricing. (2023). LAPSE:2023.10820
Author Affiliations
Guo H: School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200444, China [ORCID]
Gong D: School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200444, China [ORCID]
Zhang L: Instituto Superior Técnico, University of Lisbon, 999022 Lisbon, Portugal [ORCID]
Mo W: Shanghai Marine Equipment Research Institute, Shanghai 200031, China
Ding F: Shanghai Marine Equipment Research Institute, Shanghai 200031, China
Wang F: School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200444, China [ORCID]
Journal Name
Energies
Volume
15
Issue
15
First Page
5382
Year
2022
Publication Date
2022-07-25
ISSN
1996-1073
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Original Submission
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PII: en15155382, Publication Type: Journal Article
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LAPSE:2023.10820
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https://doi.org/10.3390/en15155382
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