Energy Science & Engineering最新文献

This study uses AVL FIRE 2020 R1 software for simulation and experimental verification to deeply analyze the impact of combustion chamber geometry and biodiesel on diesel engine performance at different injection timings. The study found that: With the advancement of injection timing, the indicated fuel consumption rate, cylinder pressure and NOx emissions of the two combustion systems increased, while the indicated thermal efficiency, temperature and Soot emissions decreased accordingly; The blending of low calorific value biodiesel will increase the indicated fuel consumption rate of the two combustion systems, but at the same time it can effectively reduce NOx and Soot emissions; The T: Turbocharger, C: Charger air cooling, D: Diesel particle filter (TCD) combustion system improves the utilization rate of cylinder air due to its unique combustion chamber geometry, thereby improving combustion performance. Compared with the Omega combustion system, the indicated thermal efficiency of the TCD combustion system increased by 6.16% to 8.38% and the indicated fuel consumption rate decreased by 5.80% to 7.73% when burning four types of fuel. In addition, the in-cylinder pressure and temperature increased, and it performed better in reducing Soot emissions. The research results show that the TCD combustion system can effectively improve the combustion and emission performance of diesel engines, provide data support for the development of diesel engine combustion systems and the combustion of oxygen-containing fuels in plateau environments, and provide an important reference for energy conservation and emission reduction.

In this experimental study, a new technique is designed and presented for controlling the rotor side converter of an induction generator (IG) for multi-rotor wind turbine (MRWT) systems. The direct power command (DPC) strategy is used to regulate the reactive and active power (Qs and Ps). DPC is characterized by several drawbacks, the most prominent of which are low durability, low current/power quality, and the use of power estimation. Therefore, a new PDPI (proportional-derivative proportional-integral) regulator is used as a suitable solution to overcome these shortcomings while maintaining simplicity, achieving a rapid dynamic response, and obtaining gains that characterize the DPC. The suggested DPC for controlling the IG inverter of an MRWT system uses two PDPI regulators and pulse width modulation (PWM) to create and generate the pulses necessary to run and regulate the IG inverter. First, the DPC-PDPI-PWM is verified in a MATLAB using different tests, and the characteristics of the DPC-PDPI-PWM is compared to that of DPC under different working conditions for a 1500 kW IG. Second, the validity of the simulated results is verified using the Hardware-in-the loop (HIL) test for the DPC-PDPI-PWM, and dSPACE 1104 is used for this purpose. The results demonstrate the effectiveness of the DPC-PDPI-PWM approach over DPC, as the harmonic distortion of the stream is minimized by 36.66%, 22.68%, and 33.33% in the three proposed tests. Also, the overshoot value of Ps was reduced compared to DPC by ratios estimated at 70.96%, 71.42%, and 70.31% in all tests. DPC-PDPI-PWM also reduces the steady-state error of Qs compared to DPC by 68.33%, 58.82%, 67.90% in all tests performed. The experimental results confirm the numerical results, suggesting that the DPC-PDPI-PWM is a suitable solution in the field of command in the future.

Lithium batteries are increasingly favored for energy storage due to their high energy density, long cycle life, and robust charge and discharge rates. However, safety concerns necessitate the implementation of a battery management system (BMS) to monitor battery status, maintain energy balance, and provide failure warnings to ensure safe operation. This paper proposes an efficient BMS for high-voltage, high-current lithium battery energy storage. The approach leverages a multihead-attention-enhanced long short-term memory (LSTM) neural network combined with an adaptive unscented Kalman filter to accurately calculate the battery's state of charge (SOC) and state of health (SOH). To improve accuracy, various factors such as temperature and internal resistance were considered. The algorithm was validated through hardware and simulation experiments, with experimental data compared to estimation results to demonstrate its precision. The findings show strong convergence and tracking capabilities, with SOC estimation presenting a maximum error of 1.5% and SOH estimation a maximum error of under 0.4%. We expect that this approach will allow for a more refined evaluation of SOC and SOH in lithium-ion batteries, potentially improving Li-ion battery system management.

With the continuous exploitation of global oil and gas resources, the focus of oilfield development has gradually shifted to low-permeability and tight reservoirs. Nowadays the nanofluid has become one of the most important methods to enhance oil recovery in low-permeability reservoir since the wettability and fluid flow characteristics can be changed as hydrophobic nanoparticles are adsorbed on the surface. In this study, we focus on the fluid slip characteristics feature of nanoparticles adsorbed with different adsorption degrees through molecular dynamics methods. Our results show that the adsorption of hydrophobic nanoparticles on the wall induces a velocity slip effect. The fluid flows in a Cassie state in the micro-channel, with a significant increase in density, velocity, and slip length. In addition, the velocity in the mainstream area is significantly greater than that near the wall. The fluid flow rate within the pore channel is maximized and the most optimal adsorption degree is around 65.08%. Meanwhile, this study provides not only of great significance for the microscopic mechanism of pressure reduction and injection enhancement technology by nanoparticles adsorbed, but also an efficient method in enhance oil recovery in low-permeability oil reservoirs.

In response to the severe problem of coal powder production in the Panhe block coalbed methane wells in the southern Qinshui Basin, the characteristics of coal powder production in the study area were identified through sample testing, indoor experiments, and theoretical calculations. The settling velocity of coal powder with different mesh sizes was clarified, and a correction factor α was proposed for the experimental and theoretical results of settling velocity. The research results indicate that the coal powder concentration in the Panhe block ranges from 0.03 to 7.14 g/L, with an average of 1.26 g/L. The particle size of the coal powder produced was 4.10–237.64 μm, with an average of 35.82 μm. The settling velocity of coal powder particles with a mesh size of 40–400 is between 0.0041 and 0.029 m/s. The larger the particle size of coal powder particles, the higher the settling velocity of coal powder; the correction coefficient ranges from 2.3 to 13.67. A corrected settling velocity calculation model was obtained by fitting the coal powder particle size data to the correction coefficient. The research results provide a theoretical basis for developing production conditions, coal powder prevention, and control measures for coalbed methane wells in the Panhe area.

Salt cavern gas storage is an important technical means to balance the demand for staggered energy supply. Due to the repeated injection and extraction of natural gas in gas storage facilities, sealing integrity failure in the wellbore of gas storage facilities frequently occurs. In response to this, considering the cyclic loading and unloading of the pressure load inside the casing, mechanical tests of set cement were carried out under alternating loads, quantifying the cumulative plastic strain change law of set cement and revealing the deterioration characteristics of its mechanical properties. A numerical model of cumulative plastic strain of casing cement sheath formation under alternating load was established based on the obtained experimental parameters. Comparative verification was conducted using experimental data, and the variation law of cumulative plastic strain of cement sheath was analyzed. The distribution of cumulative plastic strain on the cement sheath bonding surface of the entire wellbore was quantified. The research results indicate that the higher the internal pressure value of the casing, the earlier the plastic strain appears, and with the increase in the number of alternating loads, the cumulative plastic strain increases approximately linearly. After the internal pressure increased by 30 MPa, the cumulative plastic strain increased by a maximum of 46.75%. When the number of loading and unloading cycles under alternating loads is small, reducing the elastic modulus (6 GPa) of the cement sheath can effectively reduce its cumulative plastic strain. However, as the number of loading and unloading cycles under alternating loads exceeds a specific value, the cumulative plastic strain produced by high elastic modulus (15 GPa) cement sheaths decreases. Finally, the distribution pattern of cumulative plastic strain along the wellbore under different gas injection times and complex formation conditions was analyzed. Suggestions for establishing well barriers in salt cavern gas storage during cementing were proposed. The research results can provide theoretical and engineering references for evaluating the sealing integrity of gas storage wells.

In the tunnel construction project, it is possible to encounter coal mine goaf. The goaf is often accompanied by a large number of toxic and harmful gases such as gas, carbon monoxide and carbon dioxide. These factors undoubtedly increase the occurrence of geological disaster risk accidents such as gas combustion and explosion, resulting in tunnel excavation shutdown, plan delay and even a large number of casualties. To grasp the risk status of tunnel construction safety in coal mine goaf, we selected 11 risk factors as evaluation indicators on the basis of investigation and analysis of risk factors in a large number of engineering cases of tunnel crossing coal mine goaf. The construction risk evaluation indicator system of tunnel crossing coal mine goaf is constructed, the weight of construction risk evaluation indicator is calculated, and the risk evaluation grade of tunnel construction is determined. On this basis, the construction risk assessment judgment matrix is established by using the analytic hierarchy process, and the calculation system of the weight of each indicator in the risk assessment system is developed by using the Java programming language. Based on the theory of extension evaluation, a matter-element extension model for the construction risk assessment of tunnel crossing coal mine goaf is established, and the construction risk assessment of Wanmin tunnel is carried out by using this model. The results of risk assessment grade provide an important theoretical basis and guidance for the selection of safe construction methods for subsequent tunnels crossing coal mine goaf. The successful application of the matter-element extension model established in this paper provides a new idea for the quantitative evaluation of the construction risk of tunnel uncovering coal mine goaf.

The frequency of dynamic disasters is escalating in deep coal mining, with an increasing number of disasters induced by the combined static and dynamic loading. To investigate the mechanical behavior of deep sandstone under mining, cyclic disturbance, uniaxial cyclic loading, and unloading tests with equal amplitude were conducted at four different disturbance rates on the basis of static loading. The influence of loading and unloading disturbance rates on mechanical properties, fracture characteristics, acoustic emission (AE) temporal-spatial evolution, and fractal characteristics of AE spatial distribution were analyzed. The results show that the peak strength of rock samples initially decreases and then increases as the disturbance rate increases. During the cyclic loading and unloading disturbance stage, AE exhibits a significant Kaiser effect under different disturbance rates. The higher the disturbance rate, the greater the number of cycles with high amplitude AE, but fewer high amplitude AE occur during the loading to peak failure stage. The increment of the damage variable is positively correlated with the loading and unloading disturbance rate overall. The AE spatial fractal dimension in rock samples decreases under different loading and unloading disturbance rates, stabilizing at a range of 2.1–2.3. As the loading and unloading disturbance rate increases, the decreasing magnitude in fractal dimension during the cyclic loading and unloading stage first increases and then decreases, with a relatively smaller decrease during the loading to peak failure stage.

In this study, we establish a fractional-order direct drive permanent magnet synchronous wind turbines (DPMSG) model defined by Caputo based on the fractional calculus theory to overcome the singularity and limitations of integer-order DPMSG models. The path and characteristics of the DPMSG system entering the bifurcation and chaos caused by the internal parameter changes and external disturbances were analyzed. First, we established a nonlinear fractional-order mathematical model of a DPMSG system. Second, a bifurcation diagram was drawn using the maximum algorithm, and the path to chaos of the system at different orders was analyzed by combining its chaotic phase portrait and temporal sequence diagram. Subsequently, the impact of variations in the system order on the chaotic features of the original system was analyzed. The internal parameter adjustments of the system and changes in the system stability under external disturbances and other external excitations were analyzed. The influence of the system on its bifurcation phenomenon and chaotic behavior under multidimensional orders was determined, and it was observed that its path into chaos was opened by period-doubling bifurcation. Lastly, the dual-parameter stability domain of the system order corresponding to the internal parameters of the system was obtained by determining the parameter conditions for the critical stability of the system.

In recent years, photovoltaic (PV) solar energy has played a crucial role in the global transition toward renewable energy, contributing to 46% of the electric capacity. It has emerged as a primary source; however, optimizing energy utilization and solar panel efficiency to maximize absorbed solar radiation remains a significant challenge. Additionally, it addresses the optimization of solar energy generation and the mitigation of potential overheating issues in dual-axis solar tracking systems. Despite its importance, PV power generation is hindered by uncertainty and intermittency, posing obstacles to achieving a stable and reliable power supply. This research introduces an innovative synthesis method for a typical solar radiation year (TSRY) based on K-means clustering to maximize energy harvest. The K-means algorithm, a fundamental image processing technique, is utilized to classify images into distinct groups. This approach enhances energy generation potential, panel efficiency, and the long-term sustainability of solar energy systems compared to conventional methods.