China, People’s Republic

Green hydrogen produced by water electrolysis is one of the most promising technologies to realize the efficient utilization of intermittent renewable energy and the decarbonizing future. Among various electrolysis technologies the emerging anion-exchange membrane water electrolysis (AEMWE) shows the most potential for producing green hydrogen at a competitive price. In this review we demonstrate a comprehensive introduction to AEMWE including the advanced electrode design the lab-scaled testing system establishment and the electrochemical performance evaluation. Specifically recent progress in developing high activity transition metal-based powder electrocatalysts and self-supporting electrodes for AEMWE is summarized. To improve the synergistic transfer behaviors between electron charge water and gas inside the gas diffusion electrode (GDE) two optimizing strategies are concluded by regulating the pore structure and interfacial chemistry. Moreover we provide a detailed guideline for establishing the AEMWE testing system and selecting the electrolyzer components. The influences of the membrane electrode assembly (MEA) technologies and operation conditions on cell performance are also discussed. Besides diverse electrochemical methods to evaluate the activity and stability implement the failure analyses and realize the in-situ characterizations are elaborated. In end some perspectives about the optimization of interfacial environment and cost assessments have been proposed for the development of advanced and durable AEMWE.

High-accuracy gas dispersion models are necessary for predicting hydrogen movement and for reducing the damage caused by hydrogen release accidents in chemical processes. In urban areas where obstacles are large and abundant computational fluid dynamics (CFD) would be the best choice for simulating and analyzing scenarios of the accidental release of hydrogen. However owing to the large computation time required for CFD simulation it is inappropriate in emergencies and real-time alarm systems. In this study a non-linear surrogate model based on deep learning is proposed. Deep convolutional layer data-driven autoencoder and batch normalized deep neural network is used to analyze the effects of wind speed wind direction and release degree on hydrogen concentration in real-time. The typical parameters of hydrogen diffusion accidents at hydrogen refuelling stations were acquired by CFD numerical simulation approach and a database of hydrogen diffusion accident parameters is established. By establishing an appropriate neural network structure and associated activation function a deep learning framework is created and then a deep learning model is constructed. The accuracy and timeliness of the model are assessed by comparing the results of the CFD simulation with those of the deep learning model. To develop a dynamic reconfiguration prediction model for the hydrogen refuelling station diffusion scenario the algorithm is continuously enhanced and the model is improved. After training is finished the model's prediction time is measured in seconds which is 105 times quicker than field CFD simulations. The deep learning model of hydrogen release in hydrogen refuelling stations is established to realize timely and accurate prediction and simulation of accident consequences and provide decision-making suggestions for emergency rescue and personnel evacuation which is of great significance for the protection of human life health and property safety.

Low-carbon hydrogen could be an important component of a net-zero carbon economy helping to mitigate emissions in a number of hard-to-abate sectors. The United States recently introduced an escalating production tax credit (PTC) to incentivize production of hydrogen meeting increasingly stringent embodied emissions thresholds. Hydrogen produced via electrolysis can qualify for the full subsidy under current federal accounting standards if the input electricity is generated by carbon-free resources but may fail to do so if emitting resources are present in the generation mix. While use of behind-the-meter carbon-free electricity inputs can guarantee compliance with this standard the PTC could also be structured to allow producers using grid-supplied electricity to qualify subject to certain clean energy procurement requirements. Herein we use electricity system capacity expansion modeling to quantitatively assess the impact of grid-connected electrolysis on the evolution of the power sector in the western United States through 2030 under multiple possible implementations of the clean hydrogen PTC. We find that subsidized grid-connected hydrogen production has the potential to induce additional emissions at effective rates worse than those of conventional fossil-based hydrogen production pathways. Emissions can be minimized by requiring grid-based hydrogen producers to match 100% of their electricity consumption on an hourly basis with physically deliverable ‘additional’ clean generation which ensures effective emissions rates equivalent to electrolysis exclusively supplied by behind-the-meter carbon-free generation. While these requirements cannot eliminate indirect emissions caused by competition for limited clean resources which we find to be a persistent result of large hydrogen production subsidies they consistently outperform alternative approaches relying on relaxed time matching or marginal emissions accounting. Added hydrogen production costs from enforcing an hourly matching requirement rather than no requirements are less than $1 kg−1 and can be near zero if clean firm electricity resources are available for procurement.

Wind-solar hybrid hydrogen production is an effective technique route by converting the fluctuate renewable electricity into high-quality hydrogen. However the intermittency of wind and solar resources also exert chal lenges to the efficient hydrogen production. In order to address this issue this paper developed a day-ahead scheduling strategy based on multi-state transitions of the alkaline electrolyzer(AEL) which improves system flexibility by coordinating the operation of the electrolyzer with the battery. Meanwhile K-means+ + algorithm is also applied to scenario clustering and then proposed a capacity configuration method. Based on the adopted case study the wind-solar installed capacity of the designed hydrogen production system it first optimized and the power fluctuation is mitigated with the complementarity index considering volatility of 12.49%. Moreover the adopted scheduling strategy effectively reduces idle and standby states of the electrolyzer with the daily average energy utilization rate of 12 typical scenarios reaching 92.83%. In addition the wind-solar hydrogen system exhibits favorable economic potential the internal return rate and the investment payback period reach to 6.81% and 12.87 years respectively. This research provides valuable insights for efficiently producing hydrogen using renewable energy sources and promoting their synergistic operation.

With the development of energy integration technology demand response (DR) has gradually evolved into integrated demand response (IDR). In this study for the integrated energy system (IES) on the distribution grid side with electricity heat natural gas network and hydrogen energy equipment the analogy relationship between the thermal and mobile hydrogen energy storage networks is proposed. Moreover a unified model that reflects network commonalities across different energy forms is established. Then considering the time delay of the IES in the nontransient network a time-domain two-port model of the IES considering the time delay is established. This model shows the joint effect of time and space on system parameters. Finally this study validates the model in the application of DR. The verification results show that in DR the time-domain two-port model can accurately “cut peaks and fill valleys” for the IES and effectively reduce the operating cost of the IES system.

Currently the periodic inspection of composite tanks is typically achieved via hydrostatic test combined with internal and external visual inspections. Acoustic emission (AE) technology demonstrates a promising non destructive testing method for damage mode identification and damage assessment. This study focuses on AE signals characteristics and evolution behaviours for used 70 MPa Type IV hydrogen storage tanks during hydrostatic burst tests. AE-based tensile tests for epoxy resin specimen and carbon fiber tow were implemented to obtain characteristics of matrix cracking and fiber breakage. Then broadband AE sensors were used to capture AE signals during multi-step loading tests and hydrostatic burst tests. K-means ++ algorithm and wavelet packet transform are performed to cluster AE signals and verify the validity. Combining with tensile tests three clusters are manifested via matrix cracking fiber/matrix debonding and fiber breakage according to amplitude duration counts and absolute energy. The number of three clustering signals increases with the increase of pressure showing accumulated and aggravated damage. The sudden appearance of a large number of fiber breakage signals during hydrostatic burst tests suggests that the composite tank structure is becoming mechanically unstable namely the impending burst failure of the tank.

The synthesis of low-cost and highly active electrodes for both oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) is very important for water splitting. In this work the novel amorphous iron-nickel phosphide (FeP-Ni) nanocone arrays as efficient bifunctional electrodes for overall water splitting have been in-situ assembled on conductive three-dimensional (3D) Ni foam via a facile and mild liquid deposition process. It is found that the FeP-Ni electrode demonstrates highly efficient electrocatalytic performance toward overall water splitting. In 1 M KOH electrolyte the optimal FeP-Ni electrode drives a current density of 10 mA/cm2 at an overpotential of 218 mV for the OER and 120 mV for the HER and can attain such current density for 25 h without performance regression. Moreover a two-electrode electrolyzer comprising the FeP-Ni electrodes can afford 10 mA/cm2 electrolysis current at a low cell voltage of 1.62 V and maintain long-term stability as well as superior to that of the coupled RuO2/NF‖Pt/C/NF cell. Detailed characterizations confirm that the excellent electrocatalytic performances for water splitting are attributed to the unique 3D morphology of nanocone arrays which could expose more surface active sites facilitate electrolyte diffusion benefit charge transfer and also favorable bubble detachment behavior. Our work presents a facile and cost-effective pathway to design and develop active self-supported electrodes with novel 3D morphology for water electrolysis.

A potential enabler of a low carbon economy is the energy vector hydrogen. However issues associated with hydrogen storage and distribution are currently a barrier for its implementation. Hence other indirect storage media such as ammonia and methanol are currently being considered. Of these ammonia is a carbon free carrier which offers high energy density; higher than compressed air. Hence it is proposed that ammonia with its established transportation network and high flexibility could provide a practical next generation system for energy transportation storage and use for power generation. Therefore this review highlights previous influential studies and ongoing research to use this chemical as a viable energy vector for power applications emphasizing the challenges that each of the reviewed technologies faces before implementation and commercial deployment is achieved at a larger scale. The review covers technologies such as ammonia in cycles either for power or CO₂ removal fuel cells reciprocating engines gas turbines and propulsion technologies with emphasis on the challenges of using the molecule and current understanding of the fundamental combustion patterns of ammonia blends.

For commercial applications the durability and economy of the fuel cell hybrid system have become obstacles to be overcome which are not only affected by the performance of core materials and components but also closely related to the energy management strategy (EMS). This paper takes the 7.9 t fuel cell logistics vehicle as the research object and designed the EMS from two levels of qualitative and quantitative analysis which are the composite fuzzy control strategy optimized by genetic algorithm and Pontryagin’s minimum principle (PMP) optimized by objective function respectively. The cost function was constructed and used as the optimization objective to prolong the life of the power system as much as possible on the premise of ensuring the fuel economy. The results indicate that the optimized PMP showed a comprehensive optimal performance the hydrogen consumption was 3.481 kg/100 km and the cost was 13.042 $/h. The major contribution lies in that this paper presents a method to evaluate the effect of different strategies on vehicle performance including fuel economy and durability of the fuel cell and battery. The comparison between the two totally different strategies helps to find a better and effective solution to reduce the lifetime cost.

The widespread penetration of hydrogen in mainstream energy systems requires hydrogen production processes to be economically competent and environmentally efficient. Hydrogen if produced efficiently can play a pivotal role in decarbonizing the global energy systems. Therefore this study develops a framework which evaluates hydrogen production processes and quantifies deficiencies for improvement. The framework integrates slack-based data envelopment analysis (DEA) with fuzzy analytical hierarchy process (FAHP) and fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS). The proposed framework is applied to prioritize the most efficient and sustainable hydrogen production in Pakistan. Eleven hydrogen production alternatives were analyzed under five criteria including capital cost feedstock cost O&M cost hydrogen production and CO2 emission. FAHP obtained the initial weights of criteria while FTOPSIS determined the ultimate weights of criteria for each alternative. Finally slack-based DEA computed the efficiency of alternatives. Among the 11 three alternatives (wind electrolysis PV electrolysis and biomass gasification) were found to be fully efficient and therefore can be considered as sustainable options for hydrogen production in Pakistan. The rest of the eight alternatives achieved poor efficiency scores and thus are not recommended.