• Energy Research
• 7. Clean energy close
• Energies close
• Chinese Academy of Sciences close

Pyro-breaker, a fast-responding, highly reliable and explosive-driven circuit breaker, is utilized in several Quench Protection Systems (QPS). The commutation process and its parameters are the main technical considerations in the process of designing a new pyro-breaker. The commutation parameters, such as the commutation time and the current change rate, are not only determined by the electrical parameters of the commutation circuit but also the arc behavior during the operation. The arc behavior is greatly affected by the structure and the driving mechanism of the Commutation Section (CS) in the pyro-breaker. The arc model was developed decades ago and the black-box arc model is considered a valid method to study arc behavior. In this paper, the Schavemaker black-box arc model, an improved Mayr-type arc model, is applied to study the commutation process of a newly designed pyro-breaker. Unlike normal circuit breakers, the arc discussed in this paper is discharged in deionized water. A parameter selection method is proposed. The practicability of the method is verified by numerical calculation in Power Systems Computer Aided Design (PSCAD) and experimentally.

The lithium-ion battery is a complicated non-linear system with multi electrochemical processes including mass and charge conservations as well as electrochemical kinetics. The calculation process of the electrochemical model depends on an in-depth understanding of the physicochemical characteristics and parameters, which can be costly and time-consuming. We investigated the electrochemical modeling, reduction, and identification methods of the lithium-ion battery from the electrode-level to the system-level. A reduced 9th order linear model was proposed using electrode-level physicochemical modeling and the cell-level mathematical reduction method. The data-driven predictor-based subspace identification algorithm was presented for the estimation of lithium-ion battery model in the system-level. The effectiveness of the proposed modeling and identification methods was validated in an experimental study based on LiFePO4 cells. The accuracy and dynamic characteristics of the identified model were found to be much more likely related to the operating State of Charge (SOC) range. Experimental results showed that the proposed methods perform well with high precision and good robustness in the SOC range of 90% to 10%, and the tracking error increases significantly within higher (100–90%) or lower (10–0%) SOC ranges. Moreover, to achieve an optimal balance between high-precision and low complexity, statistical analysis revealed that the 6th, 3rd, and 5th order battery model is the optimal choice in the SOC range of 90% to 100%, 90% to 10%, and 10% to 0%, respectively.

Dilation behavior is of great importance for reasonable modeling of the stability of the host rock of the repository for high-level radioactive waste disposal. It is a suitable method for carrying out direct shear experiments to analyze the dilation behavior of rock with well understood physical meanings. Based on a series of direct shear experiments on granite samples from the Alxa candidate area under different normal stresses, the shear stress‒shear strain and shear stress‒normal strain relations have been studied in detail. Five typical stages have been divided associated with the fracturing process and deformation behaviors of the granite samples during the experimental process, and the method to determine the typical stress thresholds has been proposed. It has also been found that the increasing normal stress may reduce the maximum dilation angle, and when the normal stress is relatively lower, the negative dilation angle may occur during the post-peak stage. According to the data collected from the direct shear tests, an empirical model of the mobilized dilation angle dependent on normal stress and plastic shear strain is proposed. This mobilized dilation angle has clear physical meanings and can be used in plastic constitutive models of the host rock of the repository, and this analysis can also be put forward to other types of geomechanical problems, including the deformation behaviors related to landslide, earthquake, and so on.

The new energy revolution, of which the primary energy will be based on renewable energy sources and the terminal energy will be based on electric power, will have a revolutionary impact on the future power grids. In order to develop the corresponding power grid for the future energy system, first of all, the architecture and mode of operation of the future power grid must be investigated. In this paper, we suggest that the DC—dominant operation mode for transmission system, distribution network and distributed power system should be developed, and a MP-MC dominated transmission architecture (multiple powers to multiple consumers) and the two-way power exchange control (TPEC) should be employed to build “wide-area super virtual power plants” (WASVPPs) which cover all the major power plants in a wide range, allowing the consumers to obtain a stable and reliable supply of electricity from the “cloud powering” created by WASVPP and the distributed power system which is connected to the grid.

Development and utilization of deep geothermal resources, especially a hot dry rock (HDR) geothermal resource, is beneficial for both economic and environmental consideration in oilfields. This study used data from multiple sources to assess the geothermal energy resource in the Daqing Oilfield. The temperature logs in boreholes (both shallow water wells and deep boreholes) and the drilling stem test temperature were used to create isothermal maps in depths. Upon the temperature field and thermophysical parameters of strata, the heat content was calculated by 1 km × 1 km × 0.1 km cells. The result shows that in the southeastern part of Daqing Oilfield, the temperature can reach 150 °C at a depth of 3 km. The heat content within 3–5 km is 24.28 × 1021 J, wherein 68.2% exceeded 150 °C. If the recovery factor was given by 2% and the lower limit of temperature was set to be 150 °C, the most conservative estimate for recoverable HDR geothermal resource was 0.33 × 1021 J. The uncertainties of the estimation are mainly contributed to by the temperature extrapolation and the physical parameter selections.

To improve the power density and reliability of radial (RS-TLPMG) and quasi-Halbach (QH-TLPMG) magnetization tubular linear surface-mounted permanent magnet generators under realistic sea-state conditions, a novel tubular linear generator with multilayer interior permanent magnets (MI-TLPMG) for wave energy conversion is proposed and analyzed in this paper. Using finite element analysis (FEA), a comprehensive comparison of air gap flux density, flux linkage, back electromotive force (back-EMF), load, and no-load performance is investigated to verify the advantages of the proposed machine. The FEA results indicate that MI-LTPMG with a flux-concentrating effect has higher back-EMF, air gap magnetic flux density, flux linkage, and output power than do the other two machines. Finally, a prototype is manufactured and measured on the test platform and wave tank. The experiment and simulation results show a great agreement with each other.

The emissions of greenhouse gases, especially CO2, have been identified as the main contributor for global warming and climate change. Carbon capture and storage (CCS) is considered to be the most promising strategy to mitigate the anthropogenic CO2 emissions. This review aims to provide the latest developments of CO2 storage from the perspective of improving safety and economics. The mechanisms and strategies of CO2 storage, focusing on their characteristics and current status, are discussed firstly. In the second section, the strategies for assessing and ensuring the security of CO2 storage operations, including the risks assessment approach and monitoring technology associated with CO2 storage, are outlined. In addition, the engineering methods to accelerate CO2 dissolution and mineral carbonation for fixing the mobile CO2 are also compared within the second section. The third part focuses on the strategies for improving economics of CO2 storage operations, namely enhanced industrial production with CO2 storage to generate additional profit, and co-injection of CO2 with impurities to reduce the cost. Moreover, the role of multiple CCS technologies and their distribution on the mitigation of CO2 emissions in the future are summarized. This review demonstrates that CO2 storage in depleted oil and gas reservoirs could play an important role in reducing CO2 emission in the near future and CO2 storage in saline aquifers may make the biggest contribution due to its huge storage capacity. Comparing the various available strategies, CO2-enhanced oil recovery (CO2-EOR) operations are supposed to play the most important role for CO2 mitigation in the next few years, followed by CO2-enhanced gas recovery (CO2-EGR). The direct mineralization of flue gas by coal fly ash and the pH swing mineralization would be the most promising technology for the mineral sequestration of CO2. Furthermore, by accelerating the deployment of CCS projects on large scale, the government can also play its role in reducing the CO2 emissions.

The environment for practical applications of an energy storage system (ESS) in a microgrid system is very harsh, and therefore actual operating conditions become complex and changeable. In addition, the signal of the ESS sampling process contains a great deal of system and measurement noise, the sampled current fluctuates significantly, and also has high frequency. In this case, under such conditions, it is difficult to accurately estimate the state of charge (SOC) of the batteries in the ESS by common estimation methods. Therefore, this study proposes a compound SOC estimation method based on wavelet transform. This algorithm is very suitable for microgrid systems with large current, frequent fluctuating conditions, and high noise interference. The experimental results and engineering data show that the relative error of the method is 0.5%, which is much lower than the extend Kalman filter (EKF) based on wavelet transform.

The development of high-performance nonprecious metal catalysts for oxygen reduction reactions is critical for the commercialization of fuel cells. In this paper, we report a non-precious catalyst with high-performance, in which Fe and Fe3C is embedded in nitrogen-doped carbon nanofibers (MIL-N-CNFs) by co-electrospinning Fe-MIL and polyacrylonitrile (PAN) and pyrolyzing. The mass ratio of Fe-MIL to PAN in the precursors and the pyrolysis temperature were optimized to be 1.5 and treated at 800 °C, respectively. The optimized catalyst exhibited an onset potential of 0.950 V and a half-wave potential of 0.830 V in alkaline electrolytes, thanks to the improved mass transfer kinetics in a meso-porous structure and enhanced reaction kinetics by confined Fe and Fe3C particles. Additionally, the optimized catalyst showed a better methanol tolerance than the commercial 20 wt.% Pt/C, indicating a potential application in direct methanol fuel cells. Serving as the cathode in CCM, the anion-exchange membrane fuel cell reaches a power density of 192 mW cm−2 at 428 mA cm−2 and 80 °C.