Recently, Dr. Li Bei from the College of Chemistry and Environment Engineering at Shenzhen University published a research paper titled "Real-Time Hydrogen Refuelling of the Fuel Cell Electric Vehicle Through the Coupled Transportation Network and Power System" in the top journal IEEE Transactions on Intelligent Transportation Systems (Impact Factor 7.9, Zone 1 of the Chinese Academy of Sciences, TOP journal). Li Bei is the sole first author, and Shenzhen University is the first affiliation. Other authors include Jiangchen Li, Nanjing University of Aeronautics and Astronautics, China；Zhixiong Li, Opole University of Technology, Poland；Miguel Angel Sotelo, University of Alcalá, Spain.

At present, hydrogen fuel cell electric vehicle (HFCEV) is increasingly affordable to replace petrol vehicles and reduce carbon dioxide emissions. However, the refuelling of the HFCEV is still an essential problem. Specifically, there are not enough hydrogen refuelling stations at hand. In this paper, a hydrogen based microgrid is presented to produce hydrogen to refuel the HFCEV, and different strategies are proposed to guide the HFCEV’s refuelling within the coupled transportation network and power system. First, the HFCEV traffic flow model based on a real-world transportation network is presented. Then, a real-time simulation platform links the Sumo and Matlab is presented. Third, a hydrogen based microgrid to refuel HFCEV is built. Forth, an IEEE 30-node utility grid exporting power model is presented. At last, the real-time hydrogen refuelling of HFCEV through the coupled transportation network and power system is proposed. Four coupled structures are considered, and different HFCEV refuelling strategies (fixed price, dynamic price, LSTM decision price) are compared. The simulation results demonstrate that with the dynamic price, the congestion of the transportation network is improved, the waiting time is reduced by 17.71%, and the time loss of the network is reduced by 13.29%. With reasonable guidance of the price, vehicles choose the selected station to refuel hydrogen and influence the temporal-spatial distribution of the traffic flow of the transportation network. In addition, by adjusting the power station exporting power and the refuelling station importing power, the voltage condition of the power system can be improved.

Four structures are summarized as follows:：

1) In Case 1, the power station is not considered, only microgrids are considered;

2) In Case 2, the power station is considered, the exporting power of the power station is adjusted based on the selling price, and the selling price is adjusted based on the utility grid voltage; in addition, in microgrid, the hydrogen price is adjusted based on the traffic congestion;

3) In Case 3, the power station is considered, the difference is that in the microgrid, the hydrogen price is adjusted based on the utility grid voltage and the traffic congestion;

4) In Case 4, an LSTM network is adopted to train the relationship between states (voltage, traffic flow) and the price. The hydrogen price is decided based on the smart LSTM network.

In Case 1, the power station is not considered, and three different scenarios Case 1A, Case 1B, and Case 1C are implemented to compare the impact of price. In addition, in order to study the users’ behaviors impacts, three different users’ behaviors in Case 1C are further compared.

Case 1A：hydrogen price is not considered, and vehicles choose the nearest distance station to refuel hydrogen;

Case 1B：fixed hydrogen price is considered;

Case 1C：dynamic hydrogen price is considered, and the price is dynamically adjusted based on the traffic congestion. Three different users choosing refuelling station strategies are compared.

Fig. 2. The simulation structure for case 1, case 2, case 3, and case 4

The results show the traffic network states under different scenarios as presented in Table 1; the voltage deviation of the power grid is shown in the following figure.

Original Link：https://ieeexplore.ieee.org/document/10557141

Dr. Li Bei conducted scientific research at the Femto-st, FCLAB laboratory of the Centre National de la Recherche Scientifique (CNRS), France from 2015 to 2019. Currently, he serves as a teacher in the Department of Energy Science and Engineering at Shenzhen University. He has published more than 30 SCI/EI English papers as the sole first author, including 18 SCI journal papers in internationally renowned journals such as IEEE Transactions on Intelligent Transportation Systems, eTransportation, and Applied Energy, among which one is an ESI highly cited paper.