China, People’s Republic

Traditional charging stations have a single function which usually does not consider the construction of energy storage facilities and it is difficult to promote the consumption of new energy. With the gradual increase in the number of new energy vehicles (NEVs) to give full play to the complementary advantages of source-load resources and provide safe efficient and economical energy supply services this paper proposes the optimal operation strategy of a PV-charging-hydrogenation composite energy station (CES) that considers demand response (DR). Firstly the operation mode of the CES is analyzed and the CES model including a photovoltaic power generation system fuel cell hydrogen production hydrogen storage hydrogenation and charging is established. The purpose is to provide energy supply services for electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs) at the same time. Secondly according to the travel law of EVs and HFCVs the distribution of charging demand and hydrogenation demand at different periods of the day is simulated by the Monte Carlo method. On this basis the following two demand response models are established: charging load demand response based on the price elasticity matrix and interruptible load demand response based on incentives. Finally a multi-objective optimal operation model considering DR is proposed to minimize the comprehensive operating cost and load fluctuation of CES and the maximum–minimum method and analytic hierarchy process (AHP) are used to transform this into a linearly weighted single-objective function which is solved via an improved moth–flame optimization algorithm (IMFO). Through the simulation examples operation results in four different scenarios are obtained. Compared with a situation not considering DR the operation strategy proposed in this paper can reduce the comprehensive operation cost of CES by CNY 1051.5 and reduce the load fluctuation by 17.8% which verifies the effectiveness of the proposed model. In addition the impact of solar radiation and energy recharge demand changes on operations was also studied and the resulting data show that CES operations were more sensitive to energy recharge demand changes.

As one of the most promising renewable energy sources hydrogen has the excellent environmental benefit of producing zero emissions. A key technical challenge in using hydrogen across sectors is placed on its storage technology. The storage temperature of liquid hydrogen (20 K or 253 C) is close to absolute zero so the storage materials and the insulation layers are subjected to extremely stringent requirements against the cryogenic behaviour of the medium. In this context this research proposed to design a large liquid hydrogen type-C tank with AISI (American Iron and Steel Institution) type 316 L stainless steel as the metal barrier using Vapor-Cooled Shield (VCS) and Rigid Polyurethane Foams (RPF) as the insulation layer. A parametric study on the design of the insulation layer was carried out by establishing a thermodynamic model. The effects of VCS location on heat ingress to the liquid hydrogen transport tank and insulation temperature distribution were investigated and the optimal location of the VCS in the insulation was identified. Research outcomes finally suggest two optimal design schemes: (1) when the thickness of the insulation layer is determined Self-evaporation Vapor-Cooled Shield (SVCS) and Forcedevaporation Vapor-Cooled Shield (FVCS) can reduce heat transfer by 47.84% and 85.86% respectively; (2) when the liquid hydrogen evaporation capacity is determined SVCS and FVCS can reduce the thickness of the insulation layer by 50% and 67.93% respectively.

Experiments and numerical simulations were conducted to study the flame acceleration (FA) in stoichiometric CH4/H2/air mixtures with various hydrogen blend ratios (i.e. Hbr = 0% 20% 50% 80% and 100%). In the experiments high-speed photography was used to record the FA process. In the calculations the two-dimensional fully-compressible reactive Navier-Stokes equations were solved using a high-order algorithm on a dynamically adapting mesh. The chemical reaction and diffusive transport of the mixtures were described by a calibrated chemical-diffusive model. The numerical predictions are in good agreement with the experimental measurements. The results show that the mechanism of FA is similar in all cases that is the flame is accelerated by the thermal expansion effects various fluid-dynamic instabilities flame-vortex interactions and the interactions of flame with pressure waves. The hydrogen blend ratio has a significant impact on the propagation speed and the morphological evolution of the flame during FA. A larger hydrogen blend ratio leads to a faster FA and the difference in FA mainly depends on the increase of flame surface area and the interactions between flame and pressure waves. In addition as the hydrogen blend ratio increases there are fewer pockets of the unburned funnels in the combustion products when the flame propagates to the end of the channel.

Multi-energy microgrids (MEMGs) with green hydrogen have attracted significant research attention for their benefits such as energy efficiency improvement carbon emission reduction as well as line congestion alleviation. However the complexities of multi-energy networks coupled with diverse uncertainties may threaten MEMG’s operation. In this paper a data-driven methodology is proposed to achieve effective MEMG operation considering the green hydrogen technique and congestion management. First a detailed MEMG modelling approach is developed coupling with electricity green hydrogen natural gas and thermal flows. Different from conventional MEMG models hydrogen-enriched compressed natural gas (HCNG) models and weatherdependent power flow are thoroughly considered in the modelling. Meanwhile the power flow congestion problem is also formulated in the MEMG operation which could be mitigated through HCNG integration. Based on the proposed MEMG model a reinforcement learning-based method is designed to obtain the optimal solution of MEMG operation. To ensure the solution’s safety a soft actor-critic (SAC) algorithm is applied and modified by leveraging the Lagrangian relaxation and safety layer scheme. In the end case studies are conducted and presented to validate the effectiveness of the proposed method.

Proton exchange membrane water electrolysis is a core technology for green hydrogen production but its widespread adoption is hindered by a prohibitively high and uncertain life cycle cost. To address the dynamic complexity and multi-source uncertainties inherent in cost assessment this paper proposes an integrated modeling framework that combines system dynamics with an intuitionistic fuzzy bayesian network. The system dynamics model captures the macro-level feedback loops driving long-term cost evolution such as technological innovation economy-of-scale effects and other critical factors. To model and infer causal dependencies among uncertain variables that are challenging to specify precisely within the system dynamics model the intuitionistic fuzzy bayesian network is incorporated enabling quantification of relationships under conditions of incomplete data and cognitive fuzziness. Through comprehensive simulations the framework forecasts the cost evolution trajectories. Results indicate a potential 77 % reduction in the unit power cost of a 1 MW system by 2060. Uncertainty analysis revealed that the initial prediction variance for the catalyst layer was approximately 20 % significantly higher than the 6.5 % for the bipolar plate highlighting a key investment risk. A comparative analysis demonstrates that the proposed framework achieves a superior forecast accuracy with a mean absolute percentage error of 4.8 %. The proposed method provides a more accurate and robust decision support tool for long-term investment planning and policy formulation for hydrogen production through proton exchange membrane water electrolysis technology.

Fuel cell vehicles are considered as the direct alternative to fuel vehicles due to their similar driving range and refueling time. The United Nations World Forum for Harmonization of Vehicle Regulations (UN/WP29) released the Global Technical Regulation on Hydrogen and Fuel Cell Vehicles (GTR13) in July 2013 which was the first international regulation in the field of fuel cell vehicles. There exist some differences between GTR13 and the existing safety technical specifications and standards in China. This paper studied the safety requirements of the GTR13 compressed hydrogen storage system analyzed the current hydrogen storage safety standards for fuel cell vehicles in China and integrated the advantages of GTR13 to propose relevant suggestions for future revision of hydrogen storage standards for fuel cell vehicle in China.

Driven by carbon neutrality and peak carbon policies hydrogen energy due to its zeroemission and renewable properties is increasingly being used in hydrogen fuel cell vehicles (H-FCVs). However the high cost and limited durability of H-FCVs hinder large-scale deployment. Hydrogen internal combustion engine hybrid electric vehicles (H-HEVs) are emerging as a viable alternative. Research on the techno-economics of H-HEVs remains limited particularly in systematic comparisons with H-FCVs. This paper provides a comprehensive comparison of H-FCVs and H-HEVs in terms of total cost of ownership (TCO) and hydrogen consumption while proposing a multi-objective powertrain parameter optimization model. First a quantitative model evaluates TCO from vehicle purchase to disposal. Second a global dynamic programming method optimizes hydrogen consumption by incorporating cumulative energy costs into the TCO model. Finally a genetic algorithm co-optimizes key design parameters to minimize TCO. Results show that with a battery capacity of 20.5 Ah and an H-FC peak power of 55 kW H-FCV can achieve optimal fuel economy and hydrogen consumption. However even with advanced technology their TCO remains higher than that of H-HEVs. H-FCVs can only become cost-competitive if the unit power price of the fuel cell system is less than 4.6 times that of the hydrogen engine system assuming negligible fuel cell degradation. In the short term H-HEVs should be prioritized. Their adoption can also support the long-term development of H-FCVs through a complementary relationship.

One of the primary contributors to automobile exhaust pollution is the significant deviation be tween the actual and theoretical air-fuel ratios during transient conditions leading to a decrease in the conversion efficiency of three-way catalytic converters. Therefore it becomes imperative to enhance fuel economy reduce pollutant emissions and improve the accuracy of transient control over air-fuel ratio (AFR) in order to mitigate automobile exhaust pollution. In this study we propose a Linear Active Disturbance Rejection Control (LADRC) Hydrogen Doping Compensation Controller (HDC) to achieve precise control over the acceleration transient AFR of gasoline en gines. By analyzing the dynamic effects of oil film and its impact on AFR we establish a dynamic effect model for oil film and utilize hydrogen’s exceptional auxiliary combustion characteristics as compensation for fuel loss. Comparative experimental results demonstrate that our proposed algorithm can rapidly regulate the AFR close to its ideal value under three different transient conditions while exhibiting superior anti-interference capability and effectively enhancing fuel economy.

The polymer electrolyte membrane (PEM) fuel cell system is considered to be an ideal alternative for the internal combustion engine especially when used on a city bus. Hybrid buses with fuel cell systems and energy storage systems are now undergoing transit service demonstrations worldwide. A hybrid PEM fuel cell city bus with a hierarchical control system is studied in this paper. Firstly the powertrain and hierarchical control structure is introduced. Secondly the vehicle control strategy including start-stop strategy energy management strategy and fuel cell control strategy including the hydrogen system and air system control strategies are described in detail. Finally the performance of the fuel cell was analyzed based on road test data. Results showed that the different subsystems were well-coordinated. Each component functioned in concert in order to ensure that both safety and speed requirements were satisfied. The output current of the fuel cell system changed slowly and the output voltage was limited to a certain range thereby enhancing durability of the fuel cell. Furthermore the economic performance was optimized by avoiding low load conditions.

Due to the high cost of hydrogen utilization and the uncertainties in renewable energy generation and load demand significant challenges are posed for the operation optimization of hydrogen-containing integrated energy systems (IESs). In this study a robust operational model for an electric–heat–gas IES (EHG-IES) is proposed considering the hydrogen energy system heat recovery (HESHR) and multiple uncertainties. Firstly a heat recovery model for the hydrogen system is established based on thermodynamic equations and reaction principles; secondly through the constructed adjustable robust optimization (ARO) model the optimal solution of the system under the worst-case scenario is obtained; lastly the original problem is decomposed based on the column and constraint generation method and strong duality theory resulting in the formulation of a master problem and subproblem with mixed-integer linear characteristics. These problems are solved through alternating iterations ultimately obtaining the corresponding optimal scheduling scheme. The simulation results demonstrate that our model and method can effectively reduce the operation and maintenance costs of HESHR-EHG-IES while being resilient to uncertainties on both the supply and demand sides. In summary this study provides a novel approach for the diversified utilization and flexible operation of energy in HESHR-EHG-IES contributing to the safe controllable and economically efficient development of the energy market. It holds significant value for engineering practice.