Time-Decoupling Layered Optimization for Energy and Transportation Systems under Dynamic Hydrogen Pricing
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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-07-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/15/15/5382 |
| _version_ | 1827602922648633344 |
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| author | Hui Guo Dandan Gong Lijun Zhang Wenke Mo Feng Ding Fei Wang |
| author_facet | Hui Guo Dandan Gong Lijun Zhang Wenke Mo Feng Ding Fei Wang |
| author_sort | Hui Guo |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T05:28:26Z |
| format | Article |
| id | doaj.art-803e7a5330034eba85868762339341d3 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-09T05:28:26Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-803e7a5330034eba85868762339341d32023-12-03T12:34:43ZengMDPI AGEnergies1996-10732022-07-011515538210.3390/en15155382Time-Decoupling Layered Optimization for Energy and Transportation Systems under Dynamic Hydrogen PricingHui Guo0Dandan Gong1Lijun Zhang2Wenke Mo3Feng Ding4Fei Wang5School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200444, ChinaSchool of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200444, ChinaInstituto Superior Técnico, University of Lisbon, 999022 Lisbon, PortugalShanghai Marine Equipment Research Institute, Shanghai 200031, ChinaShanghai Marine Equipment Research Institute, Shanghai 200031, ChinaSchool of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200444, ChinaThe 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.https://www.mdpi.com/1996-1073/15/15/5382layered optimizationrenewable energyhydrogen-powered vehicledynamic hydrogen pricingrouting optimization |
| spellingShingle | Hui Guo Dandan Gong Lijun Zhang Wenke Mo Feng Ding Fei Wang Time-Decoupling Layered Optimization for Energy and Transportation Systems under Dynamic Hydrogen Pricing Energies layered optimization renewable energy hydrogen-powered vehicle dynamic hydrogen pricing routing optimization |
| title | Time-Decoupling Layered Optimization for Energy and Transportation Systems under Dynamic Hydrogen Pricing |
| title_full | Time-Decoupling Layered Optimization for Energy and Transportation Systems under Dynamic Hydrogen Pricing |
| title_fullStr | Time-Decoupling Layered Optimization for Energy and Transportation Systems under Dynamic Hydrogen Pricing |
| title_full_unstemmed | Time-Decoupling Layered Optimization for Energy and Transportation Systems under Dynamic Hydrogen Pricing |
| title_short | Time-Decoupling Layered Optimization for Energy and Transportation Systems under Dynamic Hydrogen Pricing |
| title_sort | time decoupling layered optimization for energy and transportation systems under dynamic hydrogen pricing |
| topic | layered optimization renewable energy hydrogen-powered vehicle dynamic hydrogen pricing routing optimization |
| url | https://www.mdpi.com/1996-1073/15/15/5382 |
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