| Autor: |
Zhang Xiaoxin, Chen Qigong, Ge Yuan |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Energy Science & Engineering, Vol 11, Iss 1, Pp 347-356 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2050-0505 |
| DOI: |
10.1002/ese3.1336 |
| Popis: |
Abstract Hydrogen fuel cell vehicles (HFCVs) are promising environmentally friendly technologies that are increasingly supported by governments around the world. In the integrated energy system (IES) of this paper, by adding the method of electrolysis to hydrogen production, the electrical energy is converted into chemical energy, which cannot only absorb the new energy with fluctuating output but also meet the use of more and more HFCVs. Aiming at the newly introduced hydrogen energy conversion and consumption pathways, this paper uses a statistical analogy to model HFVCs, taking into account the energy conversion efficiency and the needs of vehicle owners. Using the GUROBI solver in the YALMIP toolbox, the IES optimization problem is formed into a MILP problem and solved, and the corresponding co‐optimization scheduling method is given. Based on meeting the needs of HFCVs and electric vehicle (EV) owners, the system can schedule the number and timing of charging and discharging of EVs and the power of hydrogen production from electrolyzers on the time scale, and finally smooth the total power curve. Simulation results show that the proposed collaborative optimal energy scheduling method can meet the current demand for new energy in the system and improve the economy of the IES. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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