Multi-period planning of hydrogen refuelling stations using flow data: A case study for Istanbul

Decreasing energy resources is among the future concerns of almost all sectors, including transportation. Hydrogen is one of the major alternatives. Although the promotion of hydrogen fuel cell vehicles (HFCVs) is supported by the governments and automobile companies, hydrogen refuelling stations (HRSs) should be accessible in order for HFCV to become widespread. Therefore the location and the number of HRS play an essential role for the spread of the HFCVs. In this study, we aim to find the number and the location of HRSs to be operated in Istanbul by using a multi-period p-median model. The adaptation to hydrogen technology for each district of the city is modelled using human development index, a measure for life quality which is then used to determine the HFCVs’ demand based on traffic flow data. It turns out that ignoring the transition of adopting hydrogen technology may result in a significant loss. HRSs have a cluster-like structure which is due to the demographic structure of the city. One cluster of stations serves to the underpopulated region (at the peripherals) and the other cluster is located at the densely populated districts (the middle regions of the city). It turns out that instead of spreading from the center to the city boundary, the stations appear at both clusters from early periods of the 30 years planning horizon.     

Dynamic planning and energy management strategy of integrated charging and hydrogen refueling at highway energy supply stations considering on-site green hydrogen production

The layout of electric vehicles charging stations and hydrogen refueling stations (HRSs) is more and more necessary with the development of electric vehicles (EVs) and progress in hydrogen energy storage technology. Due to the high costs of HRSs and the low demand for hydrogen, it is difficult for independent HRSs to make a profit. This study focuses on the dynamic planning of energy supply stations on highways in the medium and long term, considering the growth of EV charging demand and the change in the proportion of hydrogen fuel cell vehicles (HFCVs). Based on the perspective of renewable energy generators (REGs), this study seeks the dynamic optimal configuration and comprehensive benefits of adding HRS and battery to existing EVCS considering the travel rules of new energy vehicles (NEVs). The results show that (1) It is profitable for REGs to invest in HRSs; (2) The economy of investment in batteries by REGs depends on the source-load matching. It is feasible only when the output of renewable energy is difficult to meet the demand. (3) The business model of REGs producing hydrogen on-site and supplying both electricity and hydrogen is feasible.     

Tube-trailer consolidation strategy for reducing hydrogen refueling station costs

The rollout of hydrogen fuel cell electric vehicles (FCEVs) requires the initial deployment of an adequate network of hydrogen refueling stations (HRSs). Such deployment has proven to be challenging because of the high initial capital investment, the risk associated with such an investment, and the underutilization of HRSs in early FCEV markets. Because the compression system at an HRS represents about half of the station's initial capital cost, novel concepts that would reduce the cost of compression are needed. Argonne National Laboratory with support from the U.S. Department of Energy's (DOE) Fuel Cell Technologies Office (FCTO) has evaluated the potential for delivering hydrogen in high-pressure tube-trailers as a way of reducing HRS compression and capital costs. This paper describes a consolidation strategy for a high-pressure (250-bar) tube-trailer capable of reducing the compression cost at an HRS by about 60% and the station's initial capital investment by about 40%. The consolidation of tube-trailers at pressures higher than 250 bar (e.g., 500 bar) can offer even greater HRS cost-reduction benefits. For a typical hourly fueling-demand profile and for a given compression capacity, consolidating hydrogen within the pressure vessels of a tube-trailer can triple the station's capacity for fueling FCEVs. The high-pressure tube-trailer consolidation concept could play a major role in enabling the early, widespread deployment of HRSs because it lowers the required HRS capital investment and distributes the investment risk among the market segments of hydrogen production, delivery, and refueling.     

Exact algorithms for incremental deployment of hydrogen refuelling stations

Given the large investments required to establish hydrogen refuelling stations (HRSs) and the difficulty in forecasting the sales of fuel cell electric vehicles, incremental HRS deployment offers an efficient method of establishing hydrogen infrastructure with a sufficient load factor and low financial risk. Considering that some HRSs are already in use, this study assumed that the optimal location of a new HRS maximises its distance from existing HRSs and minimises its distance from customer demand points. Accordingly, a multi-objective location model and efficient exact solution methods were proposed to determine the optimal location of one or two new HRSs. As a case study, the solution methods were applied to supply hydrogen to an increasing captive fleet of taxis in a large metropolis such as Paris with fixed demand points. The methods can be widely applied to effectively install one or two HRSs incrementally.     

Quantitative risk assessment using a Japanese hydrogen refueling station model

Although hydrogen refueling stations (HRSs) are becoming widespread across Japan and are essential for the operation of fuel cell vehicles, they present potential hazards. A large number of accidents such as explosions or fires have been reported, rendering it necessary to conduct a number of qualitative and quantitative risk assessments for HRSs. Current safety codes and technical standards related to Japanese HRSs have been established based on the results of a qualitative risk assessment and quantitative effectiveness validation of safety measures over ten years ago. In the last decade, there has been much development in the technologies of the components or facilities used in domestic HRSs and much operational experience as well as knowledge to use hydrogen in HRSs safely have been gained through years of commercial operation. The purpose of the present study is to conduct a quantitative risk assessment (QRA) of the latest HRS model representing Japanese HRSs with the most current information and to identify the most significant scenarios that pose the greatest risks to the physical surroundings in the HRS model. The results of the QRA show that the risk contours of 10^?3 and 10^?4 per year were confined within the HRS boundaries, whereas the risk contours of 10^?5 and 10^?6 per year are still present outside the HRS. Comparing the breakdown of the individual risks (IRs) at the risk ranking points, we conclude that the risk of jet fire demonstrates the highest contribution to the risks at all of the risk ranking points and outside the station. To reduce these risks and confine the risk contour of 10^?6 per year within the HRS boundaries, it is necessary to consider risk mitigation measures for jet fires.     

Review on equipment configuration and operation process optimization of hydrogen refueling station

The construction of hydrogenation infrastructure is important to promote the large-scale development of hydrogen energy industry. The technical performance of hydrogen refueling station (HRS) largely determines the refueling efficiency and cost of hydrogen fuel cell vehicles. This paper systematically lists the hydrogen refueling process and the key equipment applicable in the HRS. It comprehensively reviews the key equipment configuration from the hydrogen supply, compression, storage and refueling of the HRS. On the basis of the parameter selection and quantity configuration method, the process optimization technology related to the equipment utilization efficiency and construction cost was quantitatively evaluated. Besides, the existing problems and prospects are put forward, which lays the foundation for further research on the technical economy of HRSs.     

Performance of a hydrogen refueling station in the early years of commercial fuel cell vehicle deployment

Since 2003, the National Fuel Cell Research Center at the University of California, Irvine (UCI) has operated the first U.S. publicly accessible hydrogen refueling station (HRS). During this period, the UCI HRS supported all manufacturers in the early, pre-commercialization years of the fuel cell electric vehicle (FCEV). This paper describes and analyzes the performance of the UCI HRS during the first five years of FCEV commercialization, over which time the station has dispensed the most hydrogen daily in the California network. The station performance is compared to aggregate data published by NREL for all U.S. HRSs. Using the Hydrogen Delivery Scenario Analysis Model, typical daily refueling profiles are analyzed to determine the effect on HRS design. The results show different daily refueling profiles could substantially affect HRS design and ultimately the cost of hydrogen. While technical issues have been reduced, the compressor, dispenser, and fueling rate are areas for improvement.     

Two-tier pressure consolidation operation method for hydrogen refueling station cost reduction

An operation strategy known as two-tier “pressure consolidation” of delivered tube-trailers (or equivalent supply storage) has been developed to maximize the throughput at gaseous hydrogen refueling stations (HRSs) for fuel cell electric vehicles (FCEVs). The high capital costs of HRSs and the consequent high investment risk are deterring growth of the infrastructure needed to promote the deployment of FCEVs. Stations supplied by gaseous hydrogen will be necessary for FCEV deployment in both the near and long term. The two-tier pressure consolidation method enhances gaseous HRSs in the following ways: (1) reduces the capital cost compared with conventional stations, as well as those operating according to the original pressure consolidation approach described by Elgowainy et al. (2014) [1], (2) minimizes pressure cycling of HRS supply storage relative to the original pressure consolidation approach; and (3) increases use of the station's supply storage (or delivered tube-trailers) while maintaining higher state-of-charge vehicle fills.     

Current standards and configurations for the permitting and operation of hydrogen refueling stations

The literature lacks a systematic analysis of HRS equipment and operating standards. Researchers, policymakers, and HRS operators could find this information relevant for planning the network's future expansion. This study is intended to address this information need by providing a comprehensive strategic overview of the regulations currently in place for the construction and maintenance of hydrogen fueling stations.A quick introduction to fundamental hydrogen precautions and hydrogen design is offered. The paper, therefore, provides a quick overview of hydrogen's safety to emphasize HRS standards, rules, and regulations. Both gaseous and liquid safety issues are detailed, including possible threats and installation and operating expertise.After the safety evaluation, layouts, equipment, and operating strategies for HRSs are presented, followed by a review of in-force regulations: internationally, by presenting ISO, IEC, and SAE standards, and Europeanly, by reviewing the CEN/CENELEC standards. A brief and concise analysis of Italy's HRS regulations is conducted, with the goal of identifying potential insights for strategic development and more convenient technology deployment.     

Development of a market penetration forecasting model for Hydrogen Fuel Cell Vehicles considering infrastructure and cost reduction effects

In order to cope with climate change, the development and deployment of Hydrogen Fuel Cell Vehicles (HFCVs) is becoming more important. In this study, we developed a forecasting model for HFCVs based on the generalized Bass diffusion model and a simulation model using system dynamics. Through the developed model, we could forecast that the saturation of HFCVs in Korea can be moved up 12 years compared with the US. A sensitivity analysis on external variables such as price reduction rates of HFCVs and number of hydrogen refueling stations is also conducted. The results of this study can give insights on the effects of external variables on the market penetration of HFCVs, and the developed model can also be applied to other studies in analyzing the diffusion effects of HFCVs.     

Integrated planning method of green hydrogen supply chain for hydrogen fuel cell vehicles

To satisfy the growing refueling demand of hydrogen fuel cell vehicles (HFCVs) with carbon-free hydrogen supply, this paper proposes an integrated planning method of green hydrogen supply chain. First, the k-shorted path method is introduced to analyze HFCV refueling load considering vehicle travel habits and routing diversity. Second, based on it, a two-stage integrated planning model is established to minimize the total investment and operation cost. The construction of hydrogen refueling stations, electrolysis-based hydrogen generation stations and hydrogen pipelines are coordinated with their operating constraints, constituting the green hydrogen supply chain, in which hydrogen storage is also an important part for consideration to address variable renewable power. Then, the proposed model is reformulated as a mixed integer linear programing (MILP) problem solved efficiently. Finally, the case studies are carried out on an urban area in Xi'an China to verify the validity and correctness of the proposed method. The results show that the integrated planning can realize synergy benefits. The influence of electricity prices and k values is also discussed.     

Hydrogen refuelling stations in the Netherlands: An intercomparison of quantitative risk assessments used for permitting

As of 2003, 15 hydrogen refuelling stations (HRSs) have been deployed in the Netherlands. To become established, the HRS has to go through a permitting procedure. An important document of the permitting dossier is the quantitative risk assessment (QRA) as it assesses the risks of the HRS associated to people and buildings in the vicinity of the HRS. In the Netherlands, a generic prescribed approach exists on how to perform a QRA, however specific guidelines for HRSs do not exist. An intercomparison among the QRAs of permitted HRSs has revealed significant inconsistencies on various aspects of the QRA: namely the inclusion of HRS sub-systems and components, the HRS sub-system and component considerations as predefined components, the application of failure scenarios, the determination of failure frequencies, the application of input parameters, the consideration of preventive and mitigation measures as well as information provided regarding the HRS surroundings and the societal risk. It is therefore recommended to develop specific QRA guidelines for HRSs.     

An insight into potential early adopters of hydrogen fuel-cell vehicles in Japan

With the inauguration of the world's largest green hydrogen facility, the Government of Japan is steadily advancing towards its goal of transforming into a hydrogen-based society, but the lack of interest in adopting hydrogen fuel cell vehicles (HFCVs) among consumers is noticeable. This study examines the socioeconomic profiles of 500 potential car buyers with and without interest in HFCVs. The results show that the potential early adopters of HFCVs exhibit similar trends of sex, employment status, number of people in the households, weekly distance traveled, and frequency of using expressways that influence their decision. They have a significant variance in income, previous battery electric vehicle (BEV) experiences, and knowledge of HFCVs. The results suggest that knowledge of HFCVs and related technologies, and previous experience in driving BEVs encourage respondents to purchase HFCVs. The study suggests that the greater awareness of HFCV can assist policymakers in the successful market adoption.     

Construction of a structural equation model to identify public acceptance factors for hydrogen refueling stations under the provision of risk and safety information

Hydrogen refueling stations (HRSs) are an inevitable infrastructure for the utility of fuel cell vehicles; however, they can raise public safety concerns. The aim of this study is to establish a framework for public acceptance of HRSs in Japan upon the provision of risk and/or safety measure information on HRSs. We executed an in-person interview survey asking the respondents about their acceptance of HRSs and then constructed a structural equation model on HRS acceptance with four endogenous factors. The common factors to determine acceptability were “Dread” and “Independent”. “Balance” was added to the factors for the risk-informed group. If risk information was provided, people tended to judge based on their inherent sense of “Balance”; however, if it was not provided, their judgment was based on their intuitive “Dread” of HRSs or hydrogen. This study reveals risk perception characteristics and attempts to promote improved risk communication prior to HRS installation.     

Quantitative risk assessment of a hydrogen refueling station by using a dynamic physical model based on multi-physics system-level modeling

Numerous accidents in HRSs have been reported worldwide in accident databases; therefore, many researchers have performed quantitative risk assessments (QRAs) of HRSs to enable risk-informed decision making in determining the safety distances or risk mitigation measures. The HRSs, located in urban areas such as Tokyo in Japan, are situated in congested areas with tall buildings and high population density; thus, they have relatively narrow station areas. However, the QRAs are generally suitable for large plants such as nuclear power plants or chemical plants; therefore, relatively small plants or installations, such as HRSs, have not yet been considered as QRA objects. Hence, it is necessary to conduct detailed QRAs with risk analyses and reduce the applied uncertainties for relatively small plants or installations. We applied a model-based approach of risk assessment to model the HRS process using multi-physics system-level modeling and simulated a target system using Modelica—an equation-based, object-oriented modeling language that allows acausal modeling of complex cyber-physical systems The primary aim of this study was to conduct a QRA of an HRS based on multi-physics system-level modeling. First, we modeled the HRS components and physical relationships between the components using basic physical equations. Then, we elucidate a QRA based on the constructed model. The difference in the leakage rates due to the leak positions and dynamic behavior of the model parameters were calculated using the constructed model. Finally, we estimated the individual risks of all the scenarios and compared the resulting risk contours based on the constructed model that includes the hydrogen-fuel dynamic behavior with those based on the traditional model. These results indicate that it is possible to assess whether the risks around the station boundary are acceptable based on the scenario information obtained by evaluating the risks near the station.     

Does risk information change the acceptance of hydrogen refueling stations in the general Japanese population?

Hydrogen refueling stations (HRSs) are inevitable infrastructure for the utility of fuel cell vehicles, but they can raise people's safety concerns. We analyzed whether information on the risk/safety measures changed people's acceptance of HRSs. Respondents were provided those information and asked to rate their acceptance of an HRS placement either beside their home or at the gas station closest to their home. The respondents' perception of the risk of HRSs and their attitudes on environmental issues are analyzed by factor analyses. The results show that provision of the quantitative risk information and risk acceptance criteria increased the acceptability of HRS in proximity to the homes of respondents (P < 0.1) but decreased the acceptability of HRS at the nearest gas station. Factor analyses suggest that risk information on HRS alleviates the respondents' feelings of dread or uncertainty, leading to better acceptance. Our study should promote improved risk communication prior to HRS installation.     

Evaluating uncertainty in accident rate estimation at hydrogen refueling station using time correlation model

Hydrogen, as a future energy carrier, is receiving a significant amount of attention in Japan. From the viewpoint of safety, risk evaluation is required in order to increase the number of hydrogen refueling stations (HRSs) implemented in Japan. Collecting data about accidents in the past will provide a hint to understand the trend in the possibility of accidents occurrence by identifying its operation time However, in new technology; accident rate estimation can have a high degree of uncertainty due to absence of major accident direct data in the late operational period. The uncertainty in the estimation is proportional to the data unavailability, which increases over long operation period due to decrease in number of stations. In this paper, a suitable time correlation model is adopted in the estimation to reflect lack (due to the limited operation period of HRS) or abundance of accident data, which is not well supported by conventional approaches. The model adopted in this paper shows that the uncertainty in the estimation increases when the operation time is long owing to the decreasing data.     

Less is more: Robust prediction for fueling processes on hydrogen refueling stations

The monitoring of hydrogen refueling stations (HRSs) ensures the safety of their operations as well as optimal fueling performance. For a H70-T40 dispenser, a fueling process is required to control the temperature to be below 85 °C; the pressure to be under 70 MPa; and the final state-of-charge (SOC) to be between 95% and 100%. Table-based or MC (total heat capacity) formula-based fueling protocols are traditionally used to achieve such control. In this paper, we propose using a machine learning model to predict the key parameters of fueling processes: the final SOC, the final temperature, and the final pressure in the vehicle tank. To handle outliers and noise in real operation, we adopt a two-stage method. In the first stage, after clustering fueling processes using soft dynamic time warping, a small number of fueling processes are selected from a large amount of historical data. In the second stage, based on initial and current operating conditions, the final SOC, temperature, and pressure of fueling processes are predicted using three models: least absolute shrinkage and selection operator (LASSO), Gaussian process regression (GPR), and robust regression. The experiments on real operational data collected from four hydrogen refueling stations show that the robust regression model achieves better performance than LASSO and GPR for three out of the four stations, and that the robust regression model captures the normal states of regular operation. The computational time of the robust regression model is also scalable for real-time operation. Our study provides a feasible machine learning model for predicting the key fueling parameters, which facilitates the optimization of HRS operation.     

An empirical study on intention to use hydrogen fuel cell vehicles in India

Demand-side strategies for alternative energy like hydrogen require a thorough understanding of the potential customers' preferences and demand drivers. Multiple studies regarding users' attitudes, intentions, and behavior have been done towards electric vehicles in India, but none so far on hydrogen fuel cell vehicles (HFCVs). Our purpose is to inquire about the key parameters influencing the intention to use HFCVs in India. This empirical research using an online questionnaire was distributed and responses of 483 prospective customers received. To ascertain the users' intentions toward HFCVs, we applied a structural equation modelling approach through Smart-PLS 3.0. We find that perceived benefit, perceived risk, and policy interventions significantly influence the users' intention to adopt HFCV in India. The study suggests that the government must bring together the stakeholders, including automobile manufacturers, hydrogen producers, research institutions, and funding institutions, to address the bottlenecks to fast-track the hydrogen mobility system.     

Neural network based optimization for cascade filling process of on-board hydrogen tank

Compressed hydrogen storage is widely used in hydrogen fuel cell vehicles (HFCVs). Cascade filling systems can provide different pressure levels associated with various source tanks allowing for a variable mass flow rate. To meet refueling performance objectives, safe and fast filling processes must be available to HFCVs. The main objective of this paper is to establish an optimization methodology to determine the initial thermodynamic conditions of the filling system that leads to the lowest final temperature of hydrogen in the on-board storage tank with minimal energy consumption. First, a zero-dimensional lumped parameter model is established. This simplified model, implemented in Matlab/Simulink, is then used to simulate the flow of hydrogen from cascade pressure tanks to an on-board hydrogen storage tank. A neural network is then trained with model calculation results and experimental data for multi-objective optimization. It is found to have good prediction, allowing the determination of optimal filling parameters. The study shows that a cascade filling system can well refuel the on-board storage tank with constant average pressure ramp rate (APRR). Furthermore, a strong pre-cooling system can effectively lower the final temperature at a cost of larger energy consumption. By using the proposed neural network, for charging times less than 183s, the optimization procedure predicts that the inlet temperature is 259.99–266.58 K, which can effectively reduce energy consumption by about 2.5%.