Configuration planning for gaseous hydrogen refueling stations: a techno-economic assessment
Tjard Bätge et al.
Abstract
Fuel cell electric heavy-duty trucks and the corresponding hydrogen refueling stations are part of policymakers’ strategies to reduce road transport emissions. The construction of these refueling stations requires strategic planning on the configuration and, thus, the available capacity. No study in recent literature adequately considers the recovery process of gaseous hydrogen refueling stations between individual refueling events. By considering this recovery, this study systematically evaluates how random refueling demand profiles affect the thermodynamics and thereby the investment evaluation of differently configured stations. To this end, the underlying trade-off between high initial investment outlay and demand fulfillment as well as an ideal investment timing and potential future component upgrades are investigated. A simulation-based assessment and optimization approach is used. A thermodynamic model is developed to simulate discrete daily demand profiles. A mixed-integer linear program is developed to thereafter assess and optimize the configuration of the station’s components. A comprehensive number of simulation runs in different market ramp-up scenarios for heavy-duty trucks build the data basis of the case study. The configuration assessment shows that the stations’ capability to perform back-to-back refueling significantly influences the investment valuation. Under-fulfillment of demand influences the valuation significantly more than differing electricity consumption. The results suggest aligning the configuration with the growing market share of the vehicles. Additionally, the investment timing should be postponed. These investment strategies are discussed from a technical design perspective. Finally, comprehensive sensitivity analyses are conducted, and the potential impact on other supply chain stakeholders is discussed.
1 citation
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.16 × 0.4 = 0.06 |
| M · momentum | 0.53 × 0.15 = 0.08 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.