China, People’s Republic

Hydrogen-fuelled buses play an important role in the construction of low-carbon cities as a means of green travel. Beijing as a pilot city of hydrogen-fuelled buses in China is very important in the promotion of hydrogen-fuelled buses in China. Unfortunately the public acceptance of hydrogen-fuelledfuelled buses and their environmental positive externality value have not been studied. In this paper we investigated the willingness of Beijing households to pay for the promotion of hydrogen-fuelled buses and its influencing factors by means of a web-based questionnaire. The spike model was also used to estimate the willingness to pay (WTP) for hydrogen buses. The results show that the WTP of Beijing households is CNY 3.19 per trip. The value of a positive environmental externality is approximately CNY 29.15 million per trip. Household income level environmental knowledge individual environmental ethics and perceived behavioural control are the main influencing factors of WTP. Therefore policymakers should strengthen publicity efforts to increase individuals’ environmental awareness and environmental ethics and optimize the layout of hydrogen-fuelled bus schedules and riding experiences to improve individuals’ perceptual and behaviour control. Finally the positive environmental externality value of hydrogen buses should be valued which will help increase investor interest.

A distributed power system with renewable energy sources is very popular in recent years due to the rapid depletion of conventional sources of energy. Reasonable sizing for such power systems could improve the power supply reliability and reduce the annual system cost. The goal of this work is to optimize the size of a stand-alone hybrid photovoltaic (PV)/wind turbine (WT)/battery (B)/hydrogen system (a hybrid system based on battery and hydrogen (HS-BH)) for reliable and economic supply. Two objectives that take the minimum annual system cost and maximum system reliability described as the loss of power supply probability (LPSP) have been addressed for sizing HS-BH from a more comprehensive perspective considering the basic demand of load the profit from hydrogen which is produced by HS-BH and an effective energy storage strategy. An improved ant colony optimization (ACO) algorithm has been presented to solve the sizing problem of HS-BH. Finally a simulation experiment has been done to demonstrate the developed results in which some comparisons have been done to emphasize the advantage of HS-BH with the aid of data from an island of Zhejiang China.

Non grid connected wind power hydrogen production technology is of great significance for the large-scale comprehensive utilization of hydrogen energy and accelerating the development of clean energy. In this paper an electrolyzer power allocation and alternate control method for non grid connected wind power hydrogen production is proposed and the optimized control strategy are combined to predict the maximum wind power of certain time interval. While retaining the required data characteristics the instantaneous fluctuation of some wind power data is eliminated which provides a reliable basis for power distribution in the alternation control strategy of electrolyzer array. The case simulation verifies the effectiveness of the electrolyzer array control principle and the prediction of the maximum wind power. While ensuring the absorption effect and hydrogen production rate the service life and operation safety of the electrolyzer array are effectively improved by balancing the working state of each electrolyzer.

Hydrogen energy is regarded as an important way to achieve carbon emission reduction. This paper focuses on the combination of the design of the hydrogen supply chain network and the location of hydrogen refueling stations on the expressway. Based on the cost analysis of the hydrogen supply chain a multi-objective model is developed to determine the optimal scale and location of hydrogen refueling stations on the hydrogen expressway. The proposed model considers the hydrogen demand forecast hydrogen source selection hydrogen production and storage and transportation hydrogen station refueling mode etc. Taking Dalian City China as an example with offshore wind power as a reliable green hydrogen supply to select the location and capacity of hydrogen refueling stations for the hydrogen energy demonstration section of a certain expressway under multiple scenarios. The results of the case show that 4 and 5 stations are optimized on the expressway section respectively and the unit hydrogen cost is $14.3 /kg H2 and $11.8 /kg H2 respectively which are equal to the average hydrogen price in the international range. The optimization results verify the feasibility and effectiveness of the model.

With the proposal of China’s green energy strategy the research and development technologies of green energy such as wind energy and hydrogen energy are becoming more and more mature. However the phenomenon of wind abandonment and anti-peak shaving characteristics of wind turbines have a great impact on the utilization of wind energy. Therefore this study firstly builds a distributed wind-hydrogen hybrid energy system model then proposes the power dispatching optimization technology of a wind-hydrogen integrated energy system. On this basis a power allocation method based on the AUKF (adaptive unscented Kalman filter) algorithm is proposed. The experiment shows that the power allocation strategy based on the AUKF algorithm can effectively reduce the incidence of battery overcharge and overdischarge. Moreover it can effectively deal with rapid changes in wind speed. The wind hydrogen integrated energy system proposed in this study is one of the important topics of renewable clean energy technology innovation. Its grid-connected power is stable with good controllability and the DC bus is more secure and stable. Compared with previous studies the system developed in this study has effectively reduced the ratio of abandoned air and its performance is significantly better than the system with separate grid connected fans and single hydrogen energy storage. It is hoped that this research can provide some solutions for the research work on power dispatching optimization of energy systems.

Global energy and environmental issues are becoming increasingly serious and the promotion of clean energy and green transportation has become a common goal for all countries. In the logistics industry traditional fuels such as diesel and natural gas can no longer meet the requirements of energy and climate change. Hydrogen fuel cell logistics vehicles are expected to become the mainstream vehicles for future logistics because of their “zero carbon” advantages. The GREET model is computer simulation software developed by the Argonne National Laboratory in the USA. It is extensively utilized in research pertaining to the energy and environmental impact of vehicles. This research study examines four types of logistics vehicles: hydrogen fuel cell vehicles (FCVs) electric vehicles LNG-fueled vehicles and diesel-fueled vehicles. Diesel-fueled logistics vehicles are currently the most abundant type of vehicle in the logistics sector. LNG-fueled logistics vehicles are considered as a short-term alternative to diesel logistics vehicles while electric logistics vehicles are among the most popular types of new-energy vehicles currently. We analyze and compare their well-to-wheels (WTW) energy consumption and emissions with the help of GREET software and conduct lifecycle assessments (LCAs) of the four types of vehicles to analyze their energy and environmental benefits. When comparing the energy consumption of the four vehicle types electric logistics vehicles (EVs) have the lowest energy consumption with slightly lower energy consumption than FCVs. When comparing the nine airborne pollutant emissions of the four vehicle types the emissions of the FCVs are significantly lower than those of spark-ignition internal combustion engine logistics vehicles (SI ICEVs) compression-ignition direct-injection internal combustion engine logistics vehicles (CIDI ICEVs) and EVs. This study fills a research gap regarding the energy consumption and environmental impact of logistics vehicles in China.

Hydrogen has the physical and chemical characteristics of being flammable explosive and prone to leakage and its safety is the main issue faced by the promotion of hydrogen as an energy source. The most common scene in vehicle application is the longitudinal wind generated by driving and the original position of hydrogen concentration sensors (HCSs) did not consider the influence of longitudinal wind on the hydrogen leakage trajectory. In this paper the computational fluid dynamics (CFD) software STAR CCM 2021.1 is used to simulate the hydrogen leakage and diffusion trajectories of fuel cell vehicles (FCVs) at five different leakage locations the longitudinal wind speeds of 0 km/h 37.18 km/h and 114 km/h and it is concluded that longitudinal wind prolongs the diffusion time of hydrogen to the headspace and reduces the coverage area of hydrogen in the headspace with a decrease of 81.35%. In order to achieve a good detection effect of fuel cell vehicles within the longitudinal wind scene based on the simulated hydrogen concentration–time matrix the scene clustering method based on vector similarity evaluation was used to reduce the leakage scene set by 33%. Then the layout position of HCSs was optimized according to the proposed multi-scene full coverage response time minimization model and the response time was reduced from 5 s to 1 s.

Hydrogen is believed as a promising energy carrier that contributes to deep decarbonization especially for the sectors hard to be directly electrified. A grid-connected wind/hydrogen system is a typical configuration for hydrogen production. For such a system a critical barrier lies in the poor cost-competitiveness of the produced hydrogen. Researchers have found that flexible operation of a wind/hydrogen system is possible thanks to the excellent dynamic properties of electrolysis. This finding implies the system owner can strategically participate in day-ahead power markets to reduce the hydrogen production cost. However the uncertainties from imperfect prediction of the fluctuating market price and wind power reduce the effectiveness of the offering strategy in the market. In this paper we proposed a decision-making framework which is based on data-driven robust chance constrained programming (DRCCP). This framework also includes multi-layer perception neural network (MLPNN) for wind power and spot electricity price prediction. Such a DRCCP-based decision framework (DDF) is then applied to make the day-ahead decision for a wind/hydrogen system. It can effectively handle the uncertainties manage the risks and reduce the operation cost. The results show that for the daily operation in the selected 30 days offering strategy based on the framework reduces the overall operation cost by 24.36% compared to the strategy based on imperfect prediction. Besides we elaborate the parameter selections of the DRCCP to reveal the best parameter combination to obtain better optimization performance. The efficacy of the DRCCP method is also highlighted by the comparison with the chance-constrained programming method.

The cross-regional renewable hydrogen supply is significant for China to resolve the uneven distribution of renewable energy and decarbonize the transportation sector. Yet the economic comparison of various hydrogen supply routes remains obscure. This paper conducts a techno-economic analysis on six hydrogen supply routes for hydrogen refueling stations including gas-hydrogen tube-trailer gas-hydrogen pipeline liquid-hydrogen truck natural gas pipeline MeOH truck and NH3 truck. Furthermore the impacts of three critical factors are examined including electrolyzer selection transportation distance and electricity price. The results indicate that with a transport distance of 2000 km the natural gas pipeline route offers the lowest cost while the gas-hydrogen tube-trailer route is not economically feasible. The gas-hydrogen pipeline route shows outstanding cost competitiveness between 200 and 2000 km while it is greatly influenced by the utilization rate. The liquid-hydrogen truck route demonstrates great potential with the electricity price decreasing. This study may provide guidance for the development of the cross-regional renewable hydrogen supply for hydrogen refueling stations in China.

Vigorously developing an integrated energy system (IES) centered on the utilization of hydrogen energy is a crucial strategy to achieve the goal of carbon peaking and carbon neutrality. During the energy conversion process a hydrogen storage system releases a large amount of heat. By integrating a heat recovery mechanism we have developed a sophisticated hydrogen energy utilization model that accommodates multiple operational conditions and maximizes heat recovery thereby enhancing the efficiency of energy use on the supply side. To harness the potential of load-side response an integrated demand response (IDR) model accounting for price and incentives is established and a ladder-type subsidy incentive mechanism is proposed to deeply unlock load-side response capacity. Considering system economics and low carbon an IES source-load coordinated optimal scheduling model is proposed optimizing source-load coordinated operation for optimally integrated economy factoring in reward and punishment ladder-type carbon trading. Demonstrations reveal that the proposed methodology not only improves the efficiency of energy utilization but also minimizes wind energy wastage activates consumer engagement and reduces both system costs and carbon emissions thus proving the effectiveness of our optimization approach.