(630b) Cost-Optimization of Hydrogen Refueling Stations with Mechanical and Electrochemical Hydrogen Compressors

Hydrogen is regarded as a highly promising substitute for conventional fossil fuels in the automotive industry. Ensuring affordable refueling costs is essential for facilitating the successful transition to hydrogen vehicles. Refueling stations have a significant share in the overall cost among the various cost components related to hydrogen vehicles, accounting for approximately half the total hydrogen price [1]. Consequently, conducting economic assessments and optimizing the design and operation of hydrogen refueling infrastructure is important to enhance the competitiveness of hydrogen vehicles.

Out of the different units of a hydrogen refueling station (HRS), it is reported that the compressors and the cascade storage system are the main cost drivers [1]. In the literature, there are studies on optimizing the energy consumption of the HRS [2], as well as on optimizing the refueling costs [3]. Today, mechanical compressors are the most commonly used type of compressors in an HRS [4], but they have the disadvantage of high capital and maintenance cost. Recently, electrochemical hydrogen compressors (EHC) have also been proposed as a promising alternative [5]. However, it is still being determined whether and under which conditions they are competitive to the mechanical compressors in terms of capital and operating cost, and studies on optimizing their size and operation in an HRS context are missing.

To answer these questions, we first implement a dynamic model of a gaseous hydrogen refueling station in Modelica [6]. It consists of a compression unit, a cascade-storage system, a refrigeration unit, and a dispensing unit. Hydrogen is assumed to be produced on-site in a PEM electrolyzer. Three alternative process configurations are studied, which differ in the compressor used to compress hydrogen: a mechanical, an electrochemical, and a combined configuration, where the electrochemical compressor serves as the first compression stage, compressing hydrogen up to an intermediate level, followed by the mechanical compressor. For the mechanical compressor, we use well-known correlations based on the pressure ratio and the isentropic efficiency, while for the EHC we use our recently developed model [7]. We then formulate dynamic and multi-stage optimization problems, as the refueling of the vehicle tank and the refilling of the cascade-storage system is a non-continuous process. We use our in-house software DyOS [8] to solve the dynamic optimization problems. The sizes of the compressors and cascade-storage system as well as their operation are optimized for the three configurations of the hydrogen refueling station. The aim is to minimize the total cost of one refueling for different station sizes.

The optimization results show that the three configurations lead to comparable levelized costs of hydrogen dispensing. Moreover, differences in the main cost drivers among the three configurations are observed. In terms of energy consumption, the mechanical compressor exhibits the lowest energy demand, which we recently showed to be the case except at very low pressure levels [9]. At the same time, EHC has the lowest capital cost. Differences in the optimal operating points of the EHC in the electrochemical and the combined configuration are also observed, with lower temperatures and higher current densities being beneficial for the former case and vice versa. The results suggest that EHC could complement mechanical compressors in an HRS. However, it is essential to improve their energetic performance to achieve further cost reduction.

Acknowledgements

The authors gratefully acknowledge the financial support by the German Federal Ministry of Education and Research (BMBF) within the H2Cluster project HyInnoSep (grant number 03ZU1115CA).

References

[1] K. Reddi, A. Elgowainy, and E. Sutherland. “Hydrogen refueling station compression and storage optimization with tube-trailer deliveries”. In: Int. J. Hydrogen Energy 39.33 (2014), pp. 19169–19181.

[2] E. Rothuizen, W. Merida, M. Rokni, and M. Wistoft-Ibsen. “Optimization of hydrogen vehicle refueling via dynamic simulation”. In: Int. J. Hydrogen Energy 38.11 (2013), pp. 4221–4231.

[3] T. Mayer, M. Semmel, M. A. Guerrero Morales, K. M. Schmidt, A. Bauer, and J. Wind. “Techno-economic evaluation of hydrogen refueling stations with liquid or gaseous stored hydrogen”. In: Int. J. Hydrogen Energy 44.47 (2019), pp. 25809–25833.

[4] Z. Tian, H. Lv, W. Zhou, C. Zhang, and P. He. “Review on equipment configuration and operation process optimization of hydrogen refueling station”. In: Int. J. Hydrogen Energy 47.5 (2022), pp. 3033–3053.

[5] J. Zou, N. Han, J. Yan, Q. Feng, Y. Wang, Z. Zhao, J. Fan, L. Zeng, H. Li, and H. Wang. “Electrochemical Compression Technologies for High-Pressure Hydrogen: Current Status, Challenges and Perspective”. In: Electrochem. Energy Rev. 3.4 (2020), pp. 690–729.

[6] Modelica Association. https://modelica.org. Accessed: 2024-03-22.

[7] G. I. Prokopou, M. L. Mödden, A. Mitsos, and D. Bongartz. “Optimal Design and Operation of Electrochemical Hydrogen Compression”. In: Chemical Engineering Science (2024). DOI: https://doi.org/10.1016/j.ces.2024.120031.

[8] A. Caspari, A. M. Bremen, J. M. M. Faust, F. Jung, C. D. Kappatou, S. Sass, Y. Vaupel, R. Hannemann-Tamas, A. Mhamdi, and A. Mitsos. “DyOS - A Framework for Optimization of Large-Scale Differential Algebraic Equation Systems”. In: Comput. Aided Chem. Eng. 46 (2019), pp. 619–624.

[9] G. I. Prokopou, M. L. Mödden, A. Mitsos, and D. Bongartz. “Energetic Comparison of Electrochemical versus Mechanical Compression of Hydrogen”. In: Comput. Aided Chem. Eng. (2024). In press.