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Microbial fuel cells (MFCs) can potentially be utilized for power generation, but their low power density and low energy storage capabilities remain major bottlenecks for their large-scale development. In this research, a simplistic nitrogen-doped hierarchically porous carbon material (HPC-A) was developed through a one-step carbonization and activation process and was successfully hot-pressed on the carbon cloth (CC) substrate. This process fabricates capacitive bioanodes (HPC-A-CC) that can enhance electricity generation and storage in MFCs. The as-prepared HPC-A-CC anode delivered a power density of 2043.6 mW·m-2 and a cumulative total charge (Qm) of 426.4 ± 13.4C·m-2 at each cycle, which was 2.1 and 34.8 times higher than that of the plain CC anode, respectively. This was a result of the hierarchical and interconnected porous structure, improved hydrophilic surface, and increased number of active centers which host the bacteria for enhanced electron transfer. Electrochemical measurements indicated the superior electrochemical activity and capacitive behavior of the HPC-A-CC anode. Furthermore, biofilm analysis revealed that the HPC-A-CC biofilm exhibited higher cell viability and a more uniform spatial distribution. These findings not only demonstrate the potential of HPC-A-CC for power enhancement in MFCs but also provide a feasible solution to the problem of power generation and demand mismatch in MFC applications.

The psychology of sustainability in terms of sustainable development for work–family conflict (WFC) in organizations has become increasingly relevant in sustainable human resource management research, and the pursuit of sustainable creative performance is an important aspect of corporate sustainable development. Taking a regulatory focus perspective, this study integrates a moderated-mediation model to examine the relationship between work–family conflict and sustainable creative performance. Data were collected from 203 supervisor–subordinate dyads from two branches of a high-end manufacturing enterprise in Shanghai, China. The results reveal that work–family conflict has a positive effect on sustainable creative performance through job crafting, and the effect is stronger when individuals show higher promotion regulatory focus. We discuss the theoretical and practical implications of the study, along with potential future research directions.

Abstract Knocking combustion for spark-ignition engine is related to auto-ignition of a portion of the unburned fuel-air mixture. In this investigation, the detailed chemical kinetic mechanism was engaged to numerically study the auto-ignition characteristics of hydrogen-enriched methane under engine-relevant conditions. Compared with the experimental data, the USC Mech 2.0 mechanism obtained the closest agreement, and it was adopted in the sensitivity analysis, the rate of production (ROP) analysis and the reaction pathway analysis. Results showed that at high temperature and high pressure, the ignition delay times (IDs) of CH4/H2 fuel blends reduce significantly (by two orders of magnitude at most) with rising hydrogen fraction, but the decline rate is not so obvious (within 37.3%) at low temperature. The sensitivity analysis indicated that at high temperature the reaction (R1) and reactions (R2, R3) promote each other while at low temperature only the reaction (R3) unilaterally facilitates the reaction (R12). The ROP analysis implied that the decrease of IDs of methane by hydrogen addition is realized through increasing the H, O, and OH radical production. Interestingly, the IDs for CH4/H2 fuel blends show different trends at different temperature, which decrease (by 47.5% at most) at low temperature but increase (by 132.7% at most) at high temperature as the equivalence ratio rises. The sensitivity analysis showed that the ignition kinetics for CH4/H2 fuel blends more depend on the CH4 concentration at low temperature but oxygen concentration at high temperature. This investigation not only supplements the fundamental combustion studies of CH4/H2 fuel blends in elevated pressures, but also reveals the influence mechanism of hydrogen addition and equivalence ratio on the IDs of CH4/H2 fuel blends at high pressure. More importantly, it may offer fundamental insights for the control of knocking combustion of spark-ignition (SI) engine.

To meet power quality requirements, it is necessary to classify and identify the power quality of the power grid connected with renewable energy generation. S-transform (ST) is an effective method to analyze power quality in time and frequency domains. ST is widely used to detect and classify various kinds of non-stationary power quality disturbances. However, the long taper and scaling criteria of the Gaussian window in standard ST (SST) will lead to poor time domain resolution at low frequency and poor frequency resolution at high frequency. To solve the discrete side effects, it is necessary to select the optimal window function to locate the time frequency accurately. This paper proposes a modified ST (MST) method. In this method, an improved window function of energy concentration in time-frequency distribution is introduced to optimize the shape of each window function. This method determines the parameters of Gaussian window to maximize the product of energy concentration in a time-frequency domain within a given time and frequency interval, so as to improve the energy concentration. The result shows that compared with the SST with Gaussian window, ST based on the optimally concentrated window proposed in this paper has better energy concentration in time-frequency distribution.

Abstract The Renewable energy power generation capacity has been rapidly increasing in China recently. Meanwhile, the contradiction between power supply and demand is becoming increasingly more prominent due to the intermittence of renewable energies. On the other hand, on the mitigation of carbon dioxide (CO2) emissions in China needs immediate attention. Power-to-Gas (PtG), a chemical energy storage technology, can convert surplus electricity into combustible gases. Subsurface energy storage can meet the requirements of long term storage with its large capacity. This paper provides a discussion of the entire PtG energy storage technology process and the current research progress. Based on the comparative study of different geological storage schemes for synthetic methane, their respective research progress and limitations are noted. In addition, a full investigation of the distribution and implementation of global PtG and CO2 capture and storage (CCS) demonstration projects is performed. Subsequently, the opportunities and challenges of the development of this technology in China are discussed based on techno-economic and ecological effects analysis. While PtG is expected to be a revolutionary technology that will replace traditional power systems, the main issues of site selection, energy efficiency and the economy still need to be adequately addressed. Additionally, based on the comprehensive discussion of the results of the analysis, power-to-gas and subsurface energy storage implementation strategies, as well as outlook in China are presented.

The power transformer is important equipment for energy conversion and transmission in the power grid and its failure will bring significant economic losses to the power system. The hot-spot temperature is a primary factor affecting the reliability and service life of power transformers. In order to calculate the temperature distribution of oil-immersed transformer windings accurately, it is required to solve a multi-physical problem, in which the magnetic field and the fluid-temperature field are coupled. In the simulation of multi-physical field of transformer, many studies usually omit the turn-to-turn insulation of windings to simplify the oil-immersed transformer model. The purpose of this paper is to investigate the effect of the turn-to-turn insulation of windings in oil-immersed transformers on the simulation results. First, a 2D axisymmetric transformer model was established in ANSYS to study the effect of low-voltage winding turn-to-turn insulation on the magnetic field simulation results. The differences of eddy current losses in the simulation were also calculated in terms of the magnetic field simulation results. It is found that the turn-to-turn insulation does not affect the magnetic field distribution in evidence from the simulation results. Besides, the values of the magnetic field and eddy current loss appear significant differences only at both ends of the low-voltage winding. Second, the fluid-temperature field of the transformer was solved in Fluent and the turn-to-turn insulation was the controlled objective in the solution process with consideration of the difference in winding losses. The simulation results show that the turn-to-turn insulation of the winding does not change the oil flow distribution in simulation. The simulation model with turn-to-turn insulation appears a gradient in the temperature distribution of the discs and a rise in the overall temperature distribution. Moreover, this paper analyzes the possible reasons for the differences in the simulation results of the magnetic and temperature fields caused by the turn-to-turn insulation. Some results and conclusions in this paper can be used in related studies and designs.

Oil shale is a kind of potential alternative energy source for petroleum and has attracted the attention of energy researchers all over the world. Borehole hydraulic mining has more prominent advantages than both conventional open-pit mining and underground mining. It is very important to attempt to use the borehole hydraulic mining method to exploit underground oil shale. The nozzle is the key component of borehole hydraulic mining and reasonable mining parameters are also crucial in exploiting underground oil shale efficiently. The straight cone nozzle and the oil shale of Huadian area will be taken as the research objects. The self-developed, multifunctional, experimental device can test both the jet’s performance as well as the breaking of oil shale by the high-pressure water jet using the straight cone nozzle and varying structural parameters. Comprehensive analysis of the results of an orthogonal experimental design, including range analysis and variance analysis, demonstrate the optimal structural parameters of a straight cone nozzle as follows: the outlet diameter is 4 mm, the length to diameter ratio is 2.5, and the contraction angle is 60°. In addition, in order to maximize the efficiency of borehole hydraulic mining for Huadian oil shale, the non-submerged jet should be placed parallel to the oil shale bedding. These results can provide scientific and valuable references for borehole hydraulic mining of oil shale.

Vehicle speed prediction plays a critical role in energy management strategy (EMS). Based on the adaptive particle swarm optimization–least squares support vector machine (APSO-LSSVM) algorithm with BP neural network (BPNN), a novel closed-loop vehicle speed prediction system is proposed. The database of a vehicle internet platform was adopted to construct a speed prediction model based on the APSO-LSSVM algorithm. Furthermore, a BPNN is established according to the local high-precision nonlinear fitting relationship between the predicted value and error so as to correct the prediction value. Then, the results are returned to the APSO-LSSVM model for calculating the minimum fitness function, thus obtaining a closed-loop prediction system. Finally, equivalent fuel consumption minimization strategy (ECMS) based EMS was performed. According to the simulation results, the RMSE performance is 0.831 km/h within 5 s, which is over 20% higher than other performances. Additionally, the training time is 15 min within 5 s, which is advantageous over BPNN. Furthermore, fuel consumption increases by 6.95% compared with the dynamic-programming algorithm and decreased by 5.6%~10.9% compared with the low accuracy of speed prediction. Overall, the proposed method is crucial for optimizing EMS as it is not only effective in improving prediction accuracy but also capable of reducing training time.