This PDF file contains the front matter associated with SPIE Proceedings Volume 13419, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

Perovskite solar cells (PSCs) have emerged as a promising photovoltaic technology due to their high efficiency and cost-effectiveness. However, PSCs face challenges related to stability and environmental impact, limiting their widespread commercialization. In this study, we investigate the use of epoxy resin, a new organic material, to improve the stability and performance of PSCs. We demonstrate that epoxy resin can be applied to the perovskite surface, forming a protective layer that enhances stability without introducing defects. This protective layer shields the perovskite from environmental factors, such as humidity, heat, and UV light, which are known to degrade perovskites. Our findings shed light on the potential of epoxy resin as a passivation material for PSCs, paving the way for improved long-term stability and commercial viability.

In addressing operational issues such as stalling, peculiar sounds, and the uneven distribution of meshing points in the photovoltaic rotary drive reduction drive’s torus worm pair, an optimization approach is applied from a precise worm modeling perspective. At present, there is a scarcity of research focused on the design and solution algorithms for the discrete expression of helical surfaces in straight-profile torus worms. This study integrates point cloud surface reconstruction with algorithmic solutions to establish a model for worms. In the realm of precise modeling for planar double-enveloping torus worms, this method has been previously validated for its ability to significantly enhance modeling accuracy. Commencing with the principles of straight profile torus worm formation, this paper meticulously deduces a comprehensive numerical model for the worm’s working surface. The design incorporates an algorithm for discretizing the worm tooth surface, yielding a thorough point cloud dataset of the worm’s working tooth surface. Finally, considering the distribution of feature points and lines, a method for reconstructing the point cloud into surfaces is strategically devised. The reconstruction is executed through the utilization of MATLAB and UG, crafting a rapid modeling tool and producing a holistic helical worm model.

This article first constructs a two-sided supply-demand coupling model considering demand-side energy storage and establishes the comprehensive demand response elastic matrix model based on the elastic response characteristics of electric load price. Secondly, the optimal scheduling model of the integrated energy system (IES) in the park, considering the coupled response characteristics of multiple demands is constructed. By optimizing the operation parameters of equipment on supply and demand of the park, the coordinated optimization of energy in the park is realized. To conclude, the reliability and effectiveness of the model are verified by means of simulation tests.

To optimize solar energy utilization and enhance the photoelectric conversion efficiency (PCE) of PbS quantum dot solar cells, this paper uses ZnO nanorod arrays to construct the electron transport mechanism of the cells and enhance the charge transport between the device interfaces, thereby improving the photoelectric conversion efficiency. This paper systematically analyzes the influence of annealing temperatures on the ZnO nanorod array surface morphology and the photovoltaic properties of the battery devices. The results show that after introducing ZnO nanorod arrays into cells, the open-circuit voltage, short-circuit current density and fill factor rise from 0.58V to 0.64V, from 10.59mA·cm^-2 to 11.02mA·cm^-2 and from 53.1% to 55.2%, respectively. The results of impedance spectroscopy analysis show that the introduction of ZnO nanorod arrays provides a directed charge transport path, which reduces the charge transport resistance from 756.1Ω to 538.4Ω, improves the efficiency of electron transport, and elevates the photoelectric conversion efficiency from 3.26% (in the array-free structure) to 3.89%.

In the process of G-13 well production, severe wax deposition often happens, leading to wellbore plug, production reduction and even shutdown of the oil well. It is necessary to analyze the wax deposition behavior and select suitable wax-removal agents. The composition of wax sample and viscosity- temperature curve was tested and the wax deposition profile in the oil well was calculated. The influencing factors were analyzed and then four chemical wax-removal agents were tested based on industry standards. The research results indicate that there are 60.94% organic components, of which heavy components such as gum, asphaltene, and paraffin accounting for 45.75%. Large concentration of heavy components in crude oil, low production gas-oil ratio, and low water content are main factors for wax deposition behavior in G-13 well. The selection experiments of wax removers show that B-oil based wax remover is recommended if the wax dissolution rate is the main consideration, and C-oil based wax remover can be selected for a best comprehensive performance. In addition, dissolution rate experimental method for on-site wax sample was innovatively designed and proposed. This research work has important guiding significance for the on-site wax removal process of the target block.

For fractured low-permeability waterflooding sandstone reservoirs, due to the strong heterogeneity, start-up pressure gradient and anisotropy etc., there is a huge difference in the amount of water absorbed in the direction of wells around the injection well, and the effects are not uniform between injection and production wells, and the direction of water flooding is not clear. How to determine the location of the front edge, so as to analyze the range of water flooding as well as the flow priority direction, is the technical challenge faced by this type of reservoirs. In this paper, the governing and the waterflood front equation suitable for fractured low-permeability reservoirs considering the three characteristic features of startup pressure gradient, pressure sensitivity, and anisotropy at the same time are derived. In addition, the effects of these three features on the waterflood front were comparatively analyzed by an example, so as to provide a reference for the development of fractured low-permeability reservoirs.

A numerical method for calculating the gas pulsation in compressor pipelines based on the thermophysical properties of real gas has been developed. The one-dimensional flow dynamic equations for piping flow are derived under the condition of real gas working fluid. Given the pipeline element parameters and boundary conditions, the flow dynamic equations are discretized at the inner points of pipeline elements by the Lax-Wendroff scheme, and the characteristic equations are discretized at the boundary points by the trapezoidal integration scheme. Thereby the time-domain solution of flow data of pulsating gas at various pipeline locations is obtained. By developing the numerical analysis program, the calculations and analyses of gas pulsations in the interstage and exhaust pipelines of a two-stage hydrogen diaphragm compressor were performed. The pressure pulsation results agree well with the data calculated by PULS, and the relative magnitudes of different harmonic amplitudes are similar. The pressure pulsation level is highest at the outlet of the cylinder, and drops to the lowest level at the downstream snubber. Within a range of ±10% of the rated speed, the pressure pulsations at various locations fluctuate with the change in rotational speed, and the peak-to-peak value of pressure pulsation is generally lower than 10% of the average pressure. An appropriate inner diameter of the expansion tube can minimize pressure pulsation in the pipeline.

Numerical investigations are conducted to effectively analyze the propagation of premixed hydrogen air detonation in small-scaled L-shaped ducts. The initial burst pressure exhibits an important impact on the flame behavior. The higher the initial burst pressure, the higher the extremum pressures. The peak pressure in a fully closed duct is equal to the peak pressure in a semi-closed duct with the initial burst pressure three times higher. At the early stage of the burst, pressure instabilities generate temperature instabilities. Due to the thermal-diffusive effect, the arc-shaped flame front becomes the planar flame front within 5μs. At the corner of the L‐shaped ducts, pressure difference creates a vortex, which separates the interaction between the flame front and the unburned gas, and leads to the formation of a tilted flame front. The pressure difference on the cross-section plane of the ducts triggers the velocity difference, and there is flame acceleration up to Mach 2. The corner generates multiple reflections of the pressure wave, and thus, the high-temperature zone can be self-sustained.

This study investigates the diffusion characteristics and concentration distribution of hydrogen leakage in indoor environments by combining experimental methods with numerical simulations. The research focuses on the diffusion processes near walls and corners, as well as the distribution behavior of hydrogen at different leakage flow rates. Results indicate that hydrogen concentration decreases rapidly in the vertical direction during the initial stage of leakage and exhibits a symmetrical distribution laterally. At a flow rate of 10SLPM (standard liters per minute), the maximum alarm range occurs approximately 1 meter from the leakage point. Additionally, hydrogen leakage in corners shows similar behavior to that near walls but tends to accumulate more in the upper corners. The findings from both experiments and simulations are significant for optimizing the placement of indoor hydrogen sensors and enhancing the efficiency of emergency responses to hydrogen leaks.

To address the problem of renewable energy fluctuations in wind-photovoltaic (PV) power system with an electrochemical-hydrogen hybrid energy storage system, a dynamic economic dispatch method considering the operational characteristics of devices is proposed. First, the complementary characteristics of electrical energy storage and hydrogen energy storage are fully considered, and a mathematical description of the dynamic economic dispatch problem of the wind-PV power system with the hybrid energy storage system is established. Then, the dispatch problem is formulated as a Markov decision process framework, defining the system's observation state, dispatch action, and reward function. Subsequently, the dynamic economic dispatch decision is made using a dual deep Q-learning algorithm. Finally, the effectiveness of the proposed method is verified through simulation examples.

Large-scale production of hydrogen has been a challenge on our way towards greener energy consumption. The Co-B catalyst has been found to be an excellent catalyst for NaBH₄ hydrolysis in hydrogen production, but the optimal preparation method for the catalyst preparation and the factors that affect its performance remain to be explored. This paper proposed a chemical reduction method to prepare cobalt boride (Co-B) catalysts, discussed the performance of the catalyst in catalyzing sodium borohydride (NaBH₄) hydrolysis for hydrogen production as the temperature and the solvent ratio varied. The effects of the temperature and solvent ratio during synthesis on the catalytic performance were studied, and techniques including X-ray diffraction (XRD) and scanning electron microscopy (SEM) were employed to reveal the crystal structure and micromorphology of the Co-B catalyst under different temperatures and solvent ratios of synthesis; the energy-dispersive X-ray spectroscopy (EDS) was used to analyze the elemental makeup of the Co-B catalyst. The main findings of the research here are as follows. First, no phase transition was observed in the Co-B catalyst as the synthesis temperature varied; second, the specific surface area of the synthesized catalyst changed as the synthesis temperature varied, and at 100°C during synthesis, the Co-B catalyst reached a larger specific surface area and hence better catalytic performance. Therefore, a Co-B catalyst with both large pore size and large specific surface area was synthesized at 100°C using a solvent composed only of CH₂OH₂ in this study, and the prepared catalyst demonstrated high efficiency in catalyzing the hydrolysis of NaBH₄. Moreover, it was found that when the catalytic temperature was set at an appropriate value, the catalytic rate would see significant improvement. The research findings are expected to provide a solution to preparation of Co-B catalysts and improve its catalytic performance in processing of fuel products in industrial scenarios.

Metal halide chalcogenide because of its inherent advantages, chalcogenide solar cells have been rapidly developed in recent years, all-chalcogenide stacked cells can further improve the photoelectric conversion efficiency. Narrow bandgap Sn-Pb hybrid chalcogenide cells are suitable as the bottom cell of stacked cells. Such cells suffer from poor crystal quality and easy oxidation of Sn, all of which lead to low photoelectric conversion efficiency of the cells. Therefore, the preparation of high quality Sn-Pb hybrid chalcogenide solar cells is a challenging but interesting research topic. Based on the above problems, this paper experimentally prepared chalcogenide films with different tin-lead ratios, and then tested and analysed the intrinsic differences between two narrow bandgap tin-lead chalcogenides by SEM, AFM, XRD and other testing means, the chalcogenide with Sn₆Pb₄ ratio is prone to crystalline imbalance problem. the morphology of the tin-lead mixed chalcogenides films with Sn₆Pb₄ ratio is difficult to be controlled and the crystalline property is worse at the same time. The morphology of Sn₆Pb₄ ratio tin-lead mixed chalcocite film is difficult to control and the crystallinity is poor while at the same time the morphology is not good, the chalcocite is prone to form defects and vacancies in the inner part or at the interface. The Sn₅Pb₅ ratio of chalcocite shows better film quality, so that the PCE of Sn₅Pb₅ ratio of chalcocite solar cell is 21.56% which is better than that of Sn₆Pb₄ ratio of chalcocite solar cell which is 19.17%.

The research focuses on preventing coal and gas outburst problems by experimentally exploring the interactions between various coal samples and surfactants. It was found that the composite surfactant F-101 exhibits optimal performance in reducing the surface tension of aqueous solutions, while the anionic surfactant A-1 significantly improves the wettability of the coal sample surface. At a mass fraction of 0.3%, the two surfactants synergistically enhance the hydrophilicity and wettability of the coal samples. Further gas desorption experiments showed that all types of surfactants can effectively reduce gas desorption, with F-101 demonstrating the best performance, with the cumulative gas desorption amounts of anthracite, coking coal, and long-flame coal decreasing by 66.89%, 60.83%, and 65.36%, respectively, after treatment. This study emphasizes that the use of surfactants has the potential to significantly reduce mine gas desorption, providing an effective strategy for the prevention and control of coal and gas outburst.

Phase change microcapsule suspension is a solid-liquid two-phase fluid formed by encapsulating phase change materials in microcapsules and dispersing them in single-phase fluids. The suspension has fluidity and can store and release a large amount of heat within a narrow temperature range, making it significantly advantageous in thermal energy applications. This article introduces the configuration method of phase change microcapsule suspension, summarizes its enhanced heat transfer mechanism and key factors affecting heat storage and transfer performance, and analyzes the key issues in the application of phase change microcapsule suspension: stability, durability, and heat storage and transfer performance. Finally, the application of microcapsule suspension in construction, solar photovoltaic/thermal utilization, and heat dissipation of power equipment was introduced.

As an important solution to achieve the "double carbon" goal, it is of great significance to study the operation optimization of the integrated energy system. From the perspective of an integrated energy system, considering green power trading, energy sharing and the interaction between green power trading and carbon trading, the article establishes a carbon trading model considering carbon deduction in green power trading and an energy sharing library model, and proposes an integrated energy operation optimization model considering green power trading and energy sharing. Example analyses show that the model can reduce the total cost by 8.059% and carbon emissions by 11.998%. The model can realize the effect of reducing operation costs and carbon emissions to achieve the system low carbon economy operation.

Due to the volatility, intermittency, and uncertainty of new energy, the consumption and storage of new energy have become key constraints in building a clean energy system and achieving the dual carbon goals. Considering that China has abundant solar and wind energy resources and is also a region close to deserts, this article combines gravity energy storage and thermal energy storage technologies, using quicksand as the energy storage medium, and proposes a new energy storage scheme suitable for desert and Gobi areas. At the same time, based on the cost calculation method of energy storage per kilowatt hour throughout the entire life cycle, the economic and feasibility of sand lifting-thermal energy storage are analyzed, in order to provide a new idea for solving the problem of large-scale consumption of new energy in the southern Xinjiang region.

Metal halide perovskites have a wide range of industrial prospects due to their inherent advantages. Narrow bandgap (less than 1.30 eV) tin-lead hybrid perovskite cells as the base cell of all-perovskite stacked solar cells can further improve the photovoltaic conversion efficiency. This cell has many problems, including poor crystal quality and easy oxidation of Sn²⁺. Therefore, the preparation of high quality Sn-Pb hybrid perovskite solar cells is a challenging but interesting research topic. This paper specifically discusses the sensitivity analysis of perovskite films with different tin-lead ratios to oxygen and the photovoltaic performance of the devices. Firstly, the perovskite films with different tin-lead ratios were experimentally prepared, and then the intrinsic differences between the two narrow bandgap tin-lead hybrid perovskite were tested and analysed by XPS, UPS, Raman spectra, etc. The perovskite with the ratio of Sn₆Pb₄ are susceptible to oxidation by airborne oxygen and produce Sn vacancies which further cause severe P-type self-doping, thus seriously affecting the device performance and its stability. whereas Sn₅Pb₅ ratio perovskite shows better stability, and the film exhibits a weak P-type, thus, The 21.59% PCE of Sn₅Pb₅ perovskite solar cells was higher than that of Sn₆Pb₄ perovskite solar cells (19.07 %).

Accurate PV power prediction helps power stations to develop scheduling plans and maintain safety activity of the power system. Aiming at the problems of noise interference in the PV power prediction model and the unstable performance of a single prediction model, a PV power prediction method with variational modal decomposition, fox optimisation algorithm and CNN-BiLSTM is proposed. Experiments are carried out utilizing actual photovoltaic energy data from a specific location, the efficacy of the suggested model is measured numerically through metrics including the square root of the root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE). The findings indicate that the recommended model demonstrates enhanced performance when juxtaposed with alternative photovoltaic power forecasting models, offering theoretical insights for photovoltaic power forecasting challenges across various scenarios.

In order to increase the temperature of the sand therapy bed and achieve better results, this article designs a new type of sand therapy bed, which mainly uses a solar hot water system for heating. The article introduces the structure and working process of the new sand therapy bed, and verifies the heating effect of the solar sand therapy bed through experiments. The experimental results show that the solar sand therapy bed has good heating effect, which not only saves energy, but also is safe and reliable. It is a low-carbon and environmentally friendly heating device with great promotion and application value.

The valve-side bushing of the converter transformer serving as a critical interface between the converter transformer and the transmission system. It plays a pivotal role in the transmission of electrical energy within the system. In recent years, the issue of overheating faults in the valve-side bushing seriously affects the safety and reliability of power grid operation. The value-side bushing is susceptible to overheating defects due to the uneven force on the strap contacts caused by the misalignment of the plug in the installation process, which in turn causes uneven current distribution. This paper establishes a heat conduction inverse problem model based on the plug region of the value-side bushing, and takes the temperature distribution on the surface of the plug as the input quantity, and solves the inverse problem to realize the detection of the heat source inside the plug region of the bushing. By setting the contact resistance of the contacts, a local simulation model of the bushing plug region under the eccentric state is established, and the accuracy of the location distribution and intensity of the internal heat source reconstructed by the algorithm in this paper is verified by the model electro-thermal coupling simulation results.

This paper explores the use of self-dispersing TiO₂ nanoparticles for enhancing photovoltaic efficiency through self-cleaning coatings. These coatings reduce dust accumulation on solar panels, demonstrated by a 5% increase in electricity generation, thereby improving sustainability and reducing maintenance needs. The TiO₂ nanoparticles, synthesized with self-dispersing properties, were characterized using X-ray diffraction (XRD) and scanning electron microscopy (SEM) to analyze their crystal structure and surface morphology. The findings demonstrate that these nanoparticles possess notable photocatalytic properties, enabling the degradation of organic pollutants under ultraviolet light. Furthermore, measurements of coating transparency and contact angle confirmed that the coating not only maintains high transparency but also exhibits excellent self-cleaning performance. Overall, the application of TiO₂ nanoparticle coatings effectively reduces the maintenance requirements of solar panels, enhancing the sustainability and economic viability of photovoltaic systems.

Aiming at the problem of high carbon emission level of park-type comprehensive energy system, it is proposed to build a monitoring system for carbon emission in parks. The regional electricity carbon emission factor is an important basis for the accounting of indirect carbon emissions from electricity consumption by enterprises, and the reduction of carbon emissions from electricity consumption is an important part of the "3060" target. As the "double carbon" practice continues to evolve in the direction of accurate carbon control^[1], accurate measurement of carbon emissions from electricity consumption and guiding the decarbonization of electricity consumption behavior are the two key handles for carbon reduction. As the practice of "dual carbon" continues to evolve in the direction of precise carbon control, accurate measurement of carbon emissions from electricity consumption and guiding the decarbonization of electricity consumption behavior are the key grasps for the two carbon reductions, and the dynamic electricity carbon emission factor is the key bridge to carry out the construction of carbon emission monitoring.

In this paper, a dimensionless constant R_f (the ratio of the shell I.D. (cm) to the busbar O.D. (cm)) is defined to measure the relative size of the GIS (Gas Insulated Switchgear) shell and busbar, and this parameter has a large influence on the natural convection heat dissipation capability inside the gas chamber. A two-dimensional multi-physical field coupling computational model was established to study the influence mechanism of R_f on the steady state temperature rise inside the GIS, and the results show that: with the increase of R_f, the T_rise first decreases rapidly and then decreases slowly and finally tends to flatten out, i.e., there exists a critical value of R_f-threshold, and there is no obvious effect of increasing the size of the shell on the reduction of the steady state temperature rise inside the GIS when the value of R_f is larger than this value. In the internal filling of different insulating gases, different filling pressures, different current levels, the above law exists, only the specific value of the slight difference (2.5~3.25). In industrial design, it can be roughly considered that when the R_f>3, you can can take into account the design of structural compactness and more excellent temperature rise performance. The above research can provide a new constraint for GIS size design, thus simplifying the GIS design process.

A reasonable energy dispatch strategy is significant for urban energy systems with flexible power-to-gas devices to reduce carbon emissions, increase renewable energy consumption, and balance the interests between users and the grid operator. Therefore, we construct a Stackelberg game-based model for the urban energy system. Firstly, we model the flexible power-to-gas devices, carbon capture and storage device and integrated demand response in the urban energy system. Secondly, we propose a Transformer prediction model to supplement the chance constraints to solve the renewable energy uncertainty. Finally, we formulate a leader-follower Stackelberg game to mixed-integer nonlinear programming solved by CPLEX.

An insulating joint is an important accessory of a cathodic protection system and plays an important role in the safe operation of a pipeline. In this paper, failure analysis is carried out on the fracture cause of an insulated live joint with an external thread. This type of insulated joint is an assembly and the middle part is connected by the butt welding method. The failed insulated live joint with external thread breaks at the welded joint, and the failure cause is closely related to the incomplete welding of the whole circle at the root and the poor fusion quality of the weld. In addition, the welded root of the intact external thread-insulated live joint submitted for inspection is not welded through. Relevant standards are used to evaluate the service capability of the insulated joint with defects, and the suitability evaluation results are unacceptable under operating pressure and design pressure. At the same time, considering the poor fusion quality of the weld, it is recommended to choose the machine for equipment replacement.

With the intensification of the global energy crisis and environmental pressure, the optimization of energy systems in high-energy-consumption parks has become particularly critical. This paper proposes an integrated energy system (IES) operation optimization strategy for high-energy-consumption parks that comprehensively considers economy, energy efficiency and carbon emission. By constructing a multi-objective optimization model, it achieves efficient energy utilization and cost reduction while reducing environmental pollution. The study establishes the IES model, analyzes the energy equipment coupling relationship, and optimizes the energy conversion strategy. Example analyses verify the effectiveness of the strategies in improving operational efficiency and promoting green development.

In response to the volatility and intermittency of new energy generation in cold regions, as well as the impact of extreme weather on energy systems, a complementary distributed energy system energy storage optimization control method for predicting new energy output in cold regions is proposed. In response to the significant impact of harsh weather conditions such as low temperatures and freezing on new energy generation in cold regions, the uncertainty of new energy output and its impact on grid stability were first analyzed. Subsequently, a new energy output prediction method based on the PSO-LS-SVM prediction model was proposed. On this basis, the construction of a complementary distributed energy system was studied, which integrates multiple renewable energy sources such as solar and wind energy. Finally, through case verification, the complementary distributed energy system energy storage optimization control strategy proposed in this article has significant advantages in cold regions, which can effectively improve the utilization rate of new energy and the stability of the system, providing reliable guarantees for energy supply in cold regions.

As a sustainable manner of energy exploitation, direct solar harvesting for thermal-electric generation based on photothermal conversion is promising but still challenging with the development of highly efficient, scalable, and structure durable photothermal materials. Firstly, we introduce a soft and facile technology for porous graphene fabrication via laser induced forward transfer (LIFT) process. This photothermal material with unique structure has large surface areas for solar absorption. Furtherly, the resultant photothermal graphene promoted thermoelectric generator has been obtained and shows an outstanding combination of strong solar irradiation absorption (more than 97%), excellent photothermal conversion ability, and extraordinary anti-fouling performance (a large water contact angle of more than 150° and small water sliding angle of lower than 5°). A high output voltage of 144mV could also be obtained under one sun illumination (Model number of thermoelectric generators is TEC1-12710). And the highest output power of 222.1μWcm^-2 could also be calculated under one sun illumination. A robust and durable photothermal-electric generator in real-environmental is demonstrated, which shows a great potential of the photothermal materials applied in highly solar energy harvesting.

Bismuth oxide (Bi₂O₃) powders with different morphologies were successfully prepared by hydrothermal method using bismuth nitrate pentahydrate as the source and ammonia or sodium hydroxide as the mineralizing agent, and the phases and morphologies of the products were characterized by X-ray diffractometer and scanning electron microscopy, and the effects of different mineralizing agents on the phase, morphology and photocatalytic activity of the samples were studied. The results showed that sodium hydroxide and ammonia were used as mineralizing agents to obtain Bi₂O₃ in rod form and sheet form, respectively. The samples could degrade methyl orange under simulated visible light, and the photodegradation effect of the sample prepared when the ammonia addition amount was 30ml was the best, and the degradation rate could reach 96% after 90min of visible light irradiation.

Thermal management is key to ensuring the continued safe operation of energy storage systems. Good thermal management can ensure that the energy storage battery works at the right temperature, thereby improving its charging and discharging efficiency. The 280Ah lithium iron phosphate battery for was selected as the research object, and the numerical simulation model of the liquid-cooled plate battery pack was studied. Compared with the working condition with the discharge rate of 1C, under the condition of 2C, the T_min of the battery pack does not change seriously at the same speed, and the maximum temperature increases by about 2.76°C.

With the aim of reducing the carbon emissions an operational costs of integrated energy system, an optimal scheduling model of integrated energy system considering the integrated demand response is proposed, which aims at the lowest running cost of the system and the lowest carbon emission cost, respectively. The Spider Wasp Optimizer algorithm is used to solve the optimization problem. The simulation results show that considering integrated demand response can achieve a good “Peak clipping and valley filling” effect, and the Spider Wasp Optimizer algorithm can significantly reduce the system operational cost and carbon emission cost. The validity and feasibility of the algorithm are verified.

This experimental study investigates the significant impact of airborne dust deposition on the efficiency of building-integrated photovoltaic (BIPV) arrays. By examining factors influencing dust accumulation and its subsequent effects on photovoltaic (PV) performance, the research aims to optimize BIPV array configurations for improved long-term efficiency. The experiment utilized a controlled setup consisting of a 3-row by 2-column BIPV array subjected to varying wind velocities (0.13m/s to 0.65m/s) and inter-module spacing to simulate realistic dust deposition behaviors. The findings demonstrate a direct correlation between increased wind velocity and the amount of dust settling on PV panels, with higher velocities resulting in more substantial dust accumulation, particularly on front-row panels due to gravitational effects on larger dust particles. This increased dust deposition leads to a notable reduction in PV power output, with the most significant losses observed in the front row, diminishing towards the rear. Additionally, the study highlights the critical role of module spacing; at a constant wind velocity of 0.13m/s, greater spacing between rows resulted in varying degrees of dust accumulation and corresponding power loss. The experimental design included a dust deposition simulation platform, enabling precise control over environmental variables such as wind speed. The research underscores the necessity for optimized module placement to mitigate dust-related efficiency losses, ultimately improving the long-term performance and reliability of BIPV arrays.

Photoluminescence properties of Sr_3(1-x)Eu_2x(VO₄)₂ (x=0.05, 0.1, 0.2) and Sr_3(1-x)Y_2x-yEu_y(VO₄)₂ (x=1/3, y=0.1, 0.2, 0.3) have been investigated comparatively. Sr_3(1-x)Eu_2x(VO₄)₂ (x=0.05, 0.1, 0.2) samples exhibit the characteristic emission of Eu³⁺ due to the ⁵D₀-⁷F_j transitions, and the quenching concentration of Eu³⁺ is about x=0.1. When Sr²⁺ is partially substituted by Y³⁺ in the samples Sr₃(1-x)Y2_x-yEu_y(VO₄)₂ (x=1/3, y=0.1, 0.2, 0.3), the quenching concentration increases, and the emission becomes more intense. Structural analysis suggests that the improvement in both emission strength and quenching concentration caused by Y³doping is linked to a change in the Eu³⁺ ion's site-occupation within the Sr_3(1-x)Y_2x-yEu_y(VO₄)₂ lattice compared to its site-occupation in the Sr₃(1-x)Eu_2x(VO₄)₂ lattice.

This research obtained Ni-Al₂O₃ composite coatings at the copper matrix using jet electrodeposition. It characterized the surface morphology, XRD spectra, and microhardness of the coatings in order to obtain the optimal combination of process parameters for the preparation of the coatings and to further improve the comprehensive performance of the nickel-based nanocomposites. The results show that by the optimization of the parameters, the organization of the coating was effectively improved, and its mechanical properties were enhanced. A current density of 130A/dm² resulted in the smoothest surface and best performance of the prepared coatings. At this moment, the highest value of Al₂O₃ content was 10.2at%, the smallest grain size was 15.2nm, and the maximum microhardness value was 519.59HV.

Most studies on binary organic carboxylic acid phase change materials have been conducted through experimental methods. Molecular dynamics can simulate phase transition temperatures, thus guiding material design. This research focuses on the construction of a molecular system using a decanoic acid-octanoic acid binary composite phase change material, which is designed for refrigerated transport containers with a phase transition temperature range of 0-5°C. First, the theoretical values of the system’s phase transition temperature and eutectic point ratio are calculated using phase equilibrium theory and the second law of thermodynamics. Then, the phase transition temperature, and binding energy of the phase change material are simulated using the Dreiding force field and the isothermal-isobaric ensemble (NPT). The results indicate that the simulated phase transition temperature is 274.5K, which shows a small deviation from the theoretical and experimental values. The eutectic point ratio obtained from the binding energy analysis is 3:7, which is in good agreement with the theoretically calculated eutectic point ratio.

In order to explore the single-point stress damage form of structure-integrated composite battery panels, the mechanical properties of structure-energy storage-integrated composite battery panels are simulated. In this paper, starting from the laminated structure of composite panels, through the strength and stiffness simulation of panels with different layup programs, it can be found that the strain changes of different layup programs basically satisfy the symmetric distribution form of layer-by-layer decreasing, and the difference lies in the strain expansion form of the fixed end and the external loading place. The maximum deformations of the different layup schemes all occurred at the distal non-fixed end, and the deformations gradually increased from the fixed end to the distal end with good layup and symmetry. Therefore, for the mechanical properties of composite panels, the best performance is achieved when 90° carbon fibers are the main body of the layup, the second best performance is achieved when 45° carbon fibers are interspersed with positive and negative rows, and the worst performance is achieved when 45° carbon fibers are the main body of the layup angle.

Two porous carbon materials are synthesized by adding different qualities of polyethyleneimine to chitosan. The results show that the addition of more polyethyleneimine (CM-5) has a larger surface area (959m²/g) and more nitrogen content (0.76at%) compared to the addition of less polyethyleneimine (CM-3). The morphology of the two carbon materials is similar to the close-packed morphology of grape clusters. The CO2 adsorption capacity of CM-5 (3.08mmol/g) and CM-3 (2.85mmol/g) is large, but that of CM-5 is larger, indicating that the specific surface area and nitrogen content have an impact on the adsorption performance.

Superhydrophobic bionic surface has received a lot of attention due to its functional protective effect on the substrate, such as its anti-icing effect on transmission lines. Considering the economic and industrial prospects, anodizing technology is being considered to prepare biomimetic honeycomb pore structures to achieve superhydrophobicity and anti-icing performance. In this study, sulfuric acid, oxalic acid, and phosphoric acid electrolytes were compared to prepare porous structures for hydrophobicity. In addition, the bouncing behavior of water droplets was further tested to study the kinematic characteristics of falling water droplets on the substrate and superhydrophobic surface. The results shows that the phosphate anodized nano-porous structure has the largest average pore size (262.2nm) and porosity (40.52%), endowing it with the optimal superhydrophobicity (CA of 153.6° and SA of 8.2°) and ice adhesion strength (10.3kPa). Therefore, the anodized nano-porous structures have good protective effects and application prospects in high voltage field.

In order to develop cost-effective, environmentally friendly energy alternatives, it is crucial to develop efficient artificial photosynthesis systems and to explore the storage and conversion of solar energy. This paper presents the construction of a binary composite photocatalytic material of Co₃@CdS. The catalyst, when subjected to the appropriate conditions, enables the production of hydrogen with a high degree of selectivity. Furthermore, it facilitates the conversion of benzyl alcohol (BA) to benzaldehyde (BAD) under visible light. This work provides a new research perspective for developing efficient artificial photosynthesis systems for solar energy utilization.

Redox-active covalent organic frameworks (COFs) have received much attention as promising cathode materials for rechargeable metal-ion batteries. Desirable properties such as ordered nanopores, structural diversity and environmental friendliness make them potential substitutes for the conventional inorganic layered cathodes. However, the rational design of redox active sites within the molecular backbone is challenging and remains a lack of diversity. Here, we design an imine-based covalent organic framework containing multiple benzoquinone active units. The Li||COF cells show two redox pairs associated with the benzoquinone–dilithium benzenediolate transformation at the edges and vertices of DCBH-TABQ-COF. A remarkably high theoretical specific capacity of 379.0mAh g⁻¹ is attained regarding all the carbonyl active sites. Despite these impressive features, DCBH-TABQ-COF merely achieves a specific capacity of 60mAh g⁻¹ during the initial discharge and shows significant capacity decline at a high current density of 2000mA g⁻¹. This electrochemical failure is attributed to the structural defects caused by imperfect Schiff base polycondensation.

Consequently, this article employs simulation software to model and simulate both materials and intrinsic graphene. Subsequently, we obtained the corresponding energy band diagrams, density of states diagrams, and charge transfer diagrams for both materials. The models for ammonia adsorption by both materials were then optimized, and the energy band diagrams, density of states diagrams, charge transfer, and adsorption energy of both materials post-ammonia adsorption were calculated. Based on the analysis of the calculation and experimental results, it was concluded that sulfur doping enhances the material's conductivity, ammonia adsorption, and the sensor's detection capability for ammonia.

The porcelain material used in electrical equipment is characterized by low strength and high brittleness, which are crucial factors in ensuring the safety of the equipment when subjected to stress. To enhance the mechanical properties of high-strength porcelain materials, a theoretical analysis was conducted on the strength failure characteristics of this brittle material. Through this analysis, it was determined that the strength of porcelain materials follows the Weibull distribution and size effect formula. Subsequently, bending strength tests were performed on porcelain rods and sleeves to derive the size effect formula for the bending stress of porcelain materials.

As a new material, high manganese austenitic low-temperature steel has been widely used in the field of low-temperature pressure vessels due to its excellent low-temperature performance and low cost. The content of manganese, chromium, nickel, molybdenum, tungsten and copper is the basic parameter of high manganese austenitic low-temperature steel materials, and that is crucial for product quality control. In view of the fact that the current standards cannot cover the alloy composition range of high manganese austenitic low temperature steel, the analysis method for multi-element of high manganese austenitic low temperature steel was studied based on Inductively coupled plasma atomic emission spectroscopy. Optimize and determine instrument parameters and analytical spectral lines such as RF power, atomization gas flow rate, plasma gas flow rate and observation height. The specific parameters are as follows: RF power: 1.0kW, atomization gas flow rate: 0.7L·min^-1, auxiliary gas flow: 1.0L·min^-1, plasma gas flow: 12.0L·min^-1, observation height.: 7mm, carrier gas: argon, pump speed: 12r·min^-1, stability time: 10s, reading time: 6s, lifting delay: 20s, observation mode: radial direction, repetition number: 3 times, analysis spectrum line: Mn260.568nm, Cr206.158nm, Ni231.604nm, Mo202.032nm, Cu327.395nm, W207.912nm, background correction method: fitting. Finally, a method for multi-elements of high manganese austenitic low temperature steel by inductively coupled plasma atomic emission spectrometry was established. The limitation of quantification, precision and accuracy can meet the actual inspection requirements.

With the core heat storage unit of a high-temperature solid heat storage as the study object, model effectiveness was verified using the experimental data of the heat storage. To provide data support for the heat storage brick material selection, three heat storage units were established, and their thermal performance during charge were analyzed. The results show that the generated model has satisfied effectiveness, the maximum difference of the generated simulation model is only 3.8%, confirming the applicability for subsequent simulation analysis. After 8h charge, when all bricks were MgO, there is a risk of melting in the heating wire. When all bricks were Al₂O₃, the average heat storage temperature of the unit is 50K lower than that of the unit with MgO-Al₂O₃ bricks. To ensure the heat storage with the maximum heat storage capacity, the MgO bricks and the Al₂O₃ bricks should be utilized together.

Incorporating Pt with non-precious metals, including Fe, Co, and Mn, can substantially decrease the consumption of Pt while concurrently augmenting the electrocatalytic activity. A series of carbon-supported Pt₃Mn synthesized under various annealing temperatures are prepared in this work through a facile method. The prepared Pt₃Mn/C has a small mean particle size, even distribution and showing a good alloying degree through physicochemical characterizations. Electrochemical test results demonstrate that the Pt₃Mn/C catalyst annealed at 700°C exhibits superior electrocatalytic activity compared to its counterparts in the study, significantly outperforming the commercially available Pt/C catalyst. This research successfully fabricates an efficacious binary Pt-based oxygen reduction reaction (ORR) electrocatalyst through a straightforward and uncomplicated approach, offering potential for the method's extension to the development of additional Pt-based catalytic systems.

The desiccant coated heat exchanger is a crucial component in a solid adsorption dehumidification system, using a binder to adhere the desiccant to the heat exchanger fins, enhancing dehumidification and heat transfer performances. The choice of binder is a critical factor influencing the dehumidifier’s effectiveness. The effect of different binders on the performance of the silica gel desiccant coated was investigated with polyvinyl alcohol, styrene butadiene rubber and epoxy resin as binders. And effect of the coated layer thickness and binder and desiccant mass ratio on the dehumidification performance of coated layer was examined. The results indicated that the coated layer with silica gel-aluminum plate using polyvinyl alcohol had poor adherence. Considering adsorbent quality, adherence, and adsorption performance, the coated layer with epoxy resin, thickness of 0.4mm and binder and desiccant mass ratio of 1:9 for silica gel-aluminum plate exhibited better the performance.

Graphene/carbon nanotube/silicon nanotube (GN/CNT/Si) ternary composites were synthesized by a expedient hydrothermal method. The as-prepared GN/CNT/Si composite shows three dimensional architectural structure, in which Si particles are uniformly distributed among the wrinkled graphene thin sheets and twisted carbon nanotubes. The movement of electrons and lithium ions can be accelerated through the interconnection of graphene sheets and carbon nanotubes, optimizing their transport efficiency. Electrochemical tests have shown that GN/CNT/Si composite can retain a specific discharge capacity of 760 mAh/g after 100 cycles at 0.1C. The electrochemical properties of the GN/CNT/Si composite are superior to the pristine silicon powder and graphene-nanosilicon composite.

The paper first analyzes the physical crushing mechanism of photovoltaic modules and then examines the separation effect of EVA using pyrolysis crushing. With the increase in the number of crushing cycles, the weight proportion of particle size increased by 19.5%, and the weight proportion of -0.10mm cumulative product increased by 4.8%. The weight loss rate of the -0.10mm particle size of the heated cells was the highest. Further SEM analysis of the pyrolyzed crushed materials clearly showed that, compared to the state before pyrolysis, the materials changed from block aggregates to smaller, uniformly distributed particles, without adhesive residues. The pyrolyzed crushed materials had a higher degree of particle stereoscopic structure and lower density compared to the materials before pyrolysis. EDS analysis indicated that the main elemental composition of the crushed materials changed minimally before and after heating, but the elemental distribution in the pyrolyzed materials was more uniform than before pyrolysis. This further validated that incorporating pyrolysis into the crushing process significantly enhances the separation efficiency of EVA.

The thickness of the bound water film within the porous media significantly impacts the extraction difficulty during the water injection process for developing hydrophilic reservoirs. In order to gain a comprehensive understanding of the pivotal factors that influence the formation of a bound water film in porous media and their respective degrees of influence, this paper employs the capillary bundle model as a basis for analysis. The examination commences with an analysis of the fluid forces within the capillary tubes. Subsequently, the relationship between the thickness of the bound water film and the aforementioned factors is investigated through theoretical derivation and local sensitivity analysis. The results demonstrate that the formation of a bound water film is influenced by several key factors, including displacement pressure difference, oil viscosity, oil-water interfacial tension, and contact angle. The combined effect of these four factors significantly impacts the thickness of the bound water film. The objective of this study is to provide theoretical guidance for the optimal development of hydrophilic reservoirs through the water flooding.

Solid insulation materials undertake important insulation tasks in power insulation. For the analysis of fillers in solid insulation, there are few non-destructive testing methods currently used, and the accuracy is not high. The destructive testing accuracy of samples is high, such as thermogravimetric analysis, but the operation is complicated and the testing requirements are high, which cannot meet the rapid and non-destructive testing of silicone rubber. In this paper, silicone rubber commonly used in solid insulating materials is taken as the research object, and different samples are made by changing the filler content in rubber, and a terahertz transmission detection platform is built in the laboratory to detect the samples, and the terahertz time domain signal, refractive index and terahertz absorption rate of the samples are obtained. Finally, by analysing the terahertz absorption rate of the sample, the relationship between aluminum hydroxide content and terahertz absorption rate is obtained at the characteristic frequencies of 1.21thz and 1.33thz of silicone rubber. This method can detect the content of aluminum hydroxide filler in silicone rubber in a non-contact and non-destructive way.

Cold spray is a high-speed solid-state spray technology widely used in the fields of material surface repair, coating enhancement, and repair. In battlefield environments, using this method can achieve rapid repair of battle-damaged helicopters. In this study, a finite element model of the interaction between cold spray particles and substrates was established using the commercial nonlinear dynamics software Abaqus for repairing helicopter structures with the cold spray method. This model dynamically simulated the mechanical properties of the interaction between cold spray particles and substrates, studied the deposition repair mechanism of cold spray particles, and analyzed the effects of changes in particle velocity on particle deposition characteristics. This provides a theoretical basis for improving the quality and efficiency of helicopter repairs using cold spray technology.

This study investigates the effects of graphene carbon nanotube composite conductive additives on the performance of lithium-ion battery cathode materials. Initially, it presents the traditional cathode materials, focusing on their performance characteristics. The research emphasizes the unique properties of graphene carbon nanotube additives and their impact on enhancing conductivity, capacity, and cycle stability in cathode materials. Through an experimental approach involving data collection and analysis, the findings reveal that these additives significantly improve the cathode materials' conductivity and capacity, while also bolstering cycle stability. The results are pivotal for the advanced development of lithium-ion batteries, demonstrating that graphene carbon nanotube composite conductive additives are instrumental in elevating battery performance.

The epitaxial growth of In_xGa_1-xAs thin films at different atomic incidence angles and In-Ga atomic proportions was simulated by molecular dynamics (MD) method. The surface morphology, surface roughness and atomic distribution of In_xGa_1-xAs thin films deposited at different atomic deposition angles and In-Ga atomic proportions were analyzed. The results show that reducing the incidence angle of atoms and maintaining the In atomic proportions at 0.75 are beneficial to reduce the surface roughness and make the atomic arrangement in the thin films more orderly, thus improving the surface quality of In_xGa_1-xAs thin films.

This study investigates the use of graphene oxide (GO) membranes, prepared by vacuum filtration, for separating hydrogen isotopes. Traditional methods for separating hydrogen isotopes are complex, energy-intensive, and costly, making the development of efficient and low-cost techniques important. GO membranes are notable for their selective water permeability, chemical and mechanical stability, and high selectivity in separation. In this study, GO membranes were prepared by adjusting the pH and concentration of GO dispersions, with additional UV irradiation to enhance hydrophobicity and stability. The separation performance was tested using the air-gap membrane distillation (AGMD) process. Results showed that GO membranes prepared with a dispersion concentration of 0.3mg·mL^-1 at pH 11 had the best H/D separation performance. These membranes achieved a separation factor of 1.034, a total separation factor of 1.083, and the highest permeate flux of 11.81L·m^-2·h^-1.

Developing reliable and effective hydrogen storage materials is the primary challenges to promote the utilization of hydrogen power. Metal-supported porous carbon materials coupling physisorption of porous carbon with chemisorption of metals are primary options for hydrogen storage. In this work, recent advancements in the direction of metal-supported porous carbon materials for hydrogen storage is reviewed. The hydrogen storage capacity, operating conditions, reversibility, and cycling stability for metal-supported porous carbon materials are analyzed. Approaches to significantly enhance hydrogen storage capacities and adjust the operating conditions for hydrogen adsorption/desorption are discussed. The remaining challenges and potential direction of metal-supported porous carbon materials are proposed.

The widespread use of industrial dyes poses significant environmental and health risks, necessitating the development of efficient removal methods. This study synthesized series of UIO-66 type MOFs, using the solvothermal method and applied them to investigate selective dye adsorption performance. Based on the adsorption results, UIO-66-COOH demonstrated the highest adsorption capacity for Congo Red (CR), reaching 815.0mg/g. This capacity is significantly greater compared to that of UIO-66, which was 237.5mg/g. Isotherm analysis revealed that the uptake of CR by UIO-66-COOH adhered to the Langmuir isotherm, indicating a spontaneous and exothermic reaction. The addition of functional groups markedly improved the performance of UIO-66.

In this paper, the characteristics of the metal faced sandwich plate and the advantages of using the metal faced sandwich plate as the assembled enclosure structure are introduced. Then, the sound insulation performance of metal-faced sandwich panel is further studied, focusing on the influence of different metal surface materials on the sound insulation performance of metal-faced sandwich panel. The results show that the sandwich panels with high stiffness and high density are better than those with low stiffness and low density in each frequency band.

To enhance the electrochemical performance of NVPF, a dual modification strategy involving carbon coating and Zn doping is employed to fabricate Na_3+xV_2-xZn_x(PO₄)₂F₃/C (X=0.01, 0.03, 0.05, 0.07) composite cathodes for sodium-ion batteries. Among these, the Zn²⁺ doping ratio of x=0.03 (denoted as NVPF-Zn03) exhibited the best performance, significantly enhancing the structural stability of the NVPF cathode material during cycling and improving its cycle life under high-rate cycling conditions. Furthermore, it optimized the apparent diffusion kinetics during the oxidation-reduction process. The specific capacities of NVPF-Zn03 at current rates ranging from 0.1C to 10C were respectively 132.9, 134.6, 134.4, 128.6, 116.2, 85.3, and 55.1mAh·g^-1. Notably, after 1000 cycles at an ultra-high current rate of 10C, it still maintained a discharge capacity of 40.60mAh·g^-1, with a maximum capacity retention rate of 59.9%, significantly higher than that of the undoped sample. This study provides valuable guidance for the doping and modification of NVPF.

The development of renewable energy technologies is critical to achieving carbon neutrality. Green hydrogen, as a secondary non-polluting energy source, is emerging as a major strategy and vehicle for energy development change. In this paper, through the analysis of the characteristics of various types of electrolytic water technologies, the relevant research and problems of PEMWE key component materials are highlighted, and the influence on the existence of PEMWE key materials under renewable energy loads is further discussed. In future research, it is necessary to pay attention to the main reasons of fluctuating renewable energy sources on the decay of material performance in PEMWE devices, as well as to develop new materials to enhance the adaptability and durability to fluctuating loads.

Thermoelectric materials mainly refer to a new functional material prepared by doping and compounding one or more materials with thermoelectric properties. Due to the advantages of wide sources, low price, and stable supply, cement-based materials can be combined with thermoelectric materials to prepare high thermal/electric conversion efficiency cement-based thermoelectric materials, which can meet the requirements of national low-carbon emissions policies, as well as building energy-saving and sustainable development needs. This article systematically summarizes the current research status of cement-based thermoelectric materials at home and abroad and prospects their future development direction.

Superhydrophobic coatings have attracted significant attention due to their broad application prospects in self-cleaning properties and enhancing the corrosion resistance of various materials. These coatings, characterized by water contact angles greater than 150° and sliding angles smaller than 10°, can effectively inhibit the contact between a surface and water or environmental humidity, just like lotus leaves, thereby mitigating corrosion and its associated economic losses. In this work, a possible approach to achieving superhydrophobic coatings involves the mixing of specially processed waste stone powder (called PV7) and a solution called PV22 (which is formulated from perfluoro octane and other solvents.). The superhydrophobic coating prepared by PV7 and PV22 has good performance. Electron microscope analysis shows that the optimal ratio of PV7 to PV22 is 5:2, which can form closely spaced bumps on the surface and form an efficient gas chamber. contact angle measurements confirmed the hydrophobicity of the coating, reaching a maximum contact angle of 150° at the above ratio. Water contact experiments show that the 5.0g PV7+2.0g PV22 coating group has effective waterproof ability, indicating that it has practical application potential in realizing surface self-cleaning and corrosion resistance.

Supercapacitors, as a new type of energy storage device, offer advantages such as long service life, high power density, and being clean and pollution-free, making them a current research hotspot. However, the development of supercapacitors is constrained by traditional electrode materials due to their low energy density and poor rate performance. This paper addresses this issue by synthesizing a novel metal organic frameworks (MOFs) and graphene oxide (GO) composite material (Co-BDC@GO-x, x=0, 1, 2, 3), This research found that the amount of GO added has a significant impact on the morphology and performance of the composite material. The introduction of GO can effectively increase the conductivity of the composite, forming more ion and electron transfer channels, thereby improving the electrochemical performance. When the amount of GO added is 2 mg, Co-BDC@GO-2 achieving a high specific capacitance of up to 554.4Fg^-1 at 1Ag^-1, which resulted in a 3.25-fold improvement in performance compared to pure Co-BDC. Moreover, the rate performance is excellent, maintaining 54.5% of the initial specific capacitance from 1Ag^-1 to 20Ag^-1. Experimental results demonstrate that Co-BDC@GO-2 is a potential electrode material for supercapacitors.

Pt-Ni-Au nano catalysts have a broad application prospect in the field of fuel cell catalytic materials. In this study, chloroplatinic acid, nickel nitrate hexahydrate and chloroauric acid were used as metal precursors to prepare Pt₃NiAu_x (x=0, 0.5, 1, 1.5, 2, 3) nano alloys by the sol-gel method, and their crystal structure, surface morphology and phase composition were analyzed. The results indicate that there are two main phases in Pt-Ni-Au alloy nanomaterials, namely (Au) and (Au, Pt, Ni). The addition of Au has a stabilizing effect on Pt-Ni nano particles, but it will also increase the size of nano particles. Therefore, it is necessary to prepare Pt-Ni-Au nanostructures with excellent performance by accurately controlling of Au doping amount.

Energy demand in modern cities is becoming more and more complex. Knowing its pattern can help managers make proper decisions. However, finding the pattern of large-scale spatial coverage fields, such as a whole city, is not easy. In this paper, a data-driven stacked autoencoder-based framework is proposed to capture the spatio-temporal pattern for electricity consumption. The data can be organized as a one-time series and the geography coverage of the analysis can be determined by the collected data. An experiment with collected data proves the feasibility of the framework.

With the increase in the proportion of solar power generation, reasonably arranging the power consumption time to consume the power becomes an important issue. This paper studies the low-carbon problem of combining distributed photovoltaic power generation systems with AGV-ordered charging scheduling, proposes a mathematical model for optimizing charging schedules, and applies a genetic taboo algorithm for solving it. Through numerical verification, the optimal charging interval during the working cycle is obtained. This can significantly reduce the carbon emissions.

Traditional ways of power transmission and transformation project management and application have gradually revealed their shortcomings in adapting to the complex engineering environment and improving work efficiency. To solve this problem, this paper studies the digital management and application of power transmission and transformation projects based on 3D design results. It aims to integrate design results and construction process data and establish the association relationship between models and documents with 3D models as the core. By selecting a specific component model and associating it with the corresponding construction data or documents, it realizes direct access to the model and documents, thus providing a digital management solution for the whole life cycle. This paper provides strong support for related fields, and future work will further improve the functions of digital management, expand the areas of its applications, and promote the deeper integration and development of digital technology in power transmission and transformation projects.

Electricity theft not only leads to economic losses but also poses potential risks to the stability and security of the power system, constituting a significant challenge within the electricity domain. With the construction of smart grids and the maturation of advanced metering infrastructure (AMI), numerous novel techniques for detecting electricity theft have been proposed, greatly enhancing the capability to detect and combat such illicit activities, thus fostering more efficient and intelligent management of power systems. This paper aims to provide an overview of the recent advancements in electricity theft detection methods, summarizing prevalent techniques employed in detecting electricity theft in power systems, including those based on grid state analysis, machine learning, game theory, and hardware-based approaches. For each method, an analysis of its principles and merits is conducted. Finally, this paper delves into an in-depth analysis of the challenges confronting the field of electricity theft detection at present and offers prospects for future research endeavors.

In the process of construction of high-voltage transmission line, if the tension failure occurs, it will cause serious damage to the existing facilities below. For this reason, a steel structure protection device called cross-frame is needed. The accurate prediction of the wire impacting force on the cross-frame is an important design input condition. In this investigation, the Absolute Nodal Coordinate Formulation (ANCF) cable element is used to model the power transmission wire. Since the stiffness matrix is time varying, the modal truncation-based model order reduction method cannot be directly applied. In this investigation, a local linearization method is given. The whole process of the wire motion is divided into several subdomains and the first order Tylor expansion is applied on the dynamic equation within each subdomain, making it possible to perform the modal truncation of the wire. Simulation algorithm for the protecting system is developed and tested. The distribution of the velocity and stress can be obtained. The design and operation safety of the cross-frame can be improved according to the simulation results.

A novel hot-cathode plasma sputtering technique has been established, enabling the synthesis of ITO films at low pressure while allowing for independent control of various parameters. Furthermore, the electrical characteristics of the films can be assessed in a vacuum using the Van der Pauw method. Utilizing this equipment, we explored the electrical characteristics of ITO films deposited on glass substrates from an ITO target (In₂O₃ containing 5wt% SnO₂). We analyzed how different deposition parameters influence the electrical properties of the films, and concluded that the low target voltage is important as one of influencing factors which improves the resistivity of films under certain excitation conditions of the plasma. The ITO films of low resistivity of 1.9×10⁻⁴Ωcm are synthesized at the target voltage of -200V when the working Ar pressure is 1×10⁻³Torr for the plasma excitation.

Predicting the insulation defect status of power cables is challenging, making it difficult to accurately assess the cable's operational condition. This paper presents a service life predictive model of cable defects utilizing a multiple kernel learning model. The approach includes extracting features from multi-parameter data, fusing these features, and predicting defect service life. Initially, aggregate features are derived from cable equipment's multi-parameter data. Next, the multiple kernel learning optimization algorithm determines kernel weights for different data perspectives. Lastly, the SVM algorithm projects these weights into the target space to develop a service life predictive model of cable insulation failure. The results of experiment and case studies show that this method can effectively integrates diverse cable detection data, and tracks the progression of insulation faults accurately, maintains robustness in evaluations, and achieves high accuracy. It is suitable for predicting insulation defect trends and assessing insulation conditions in different environments.

Silicone rubber material is widely used in power grid system, and the rubber content in silicone rubber is an important factor to judge insulating materials. Too high or too low rubber content will affect the insulation and mechanical properties of materials. In this paper, terahertz non-destructive testing method is used to build a terahertz testing platform in the laboratory, and the absorption rate of silicone rubber samples is obtained by transmission testing. Through DFT calculation of the main components in silicone rubber at terahertz frequency, the absorption rate at terahertz frequency is simulated, and the comparison between the measured signal and the simulated signal shows that the rubber content has a good linear relationship with the absorption rate at 1.90thz frequency, and the rubber content in silicone rubber can be obtained by this frequency.

In order to solve the shortcomings of the traditional detection method of insulating oil moisture, which is lossy testing and cumbersome detection steps, this paper realizes the non-destructive detection of insulating oil moisture using terahertz technology. Firstly, the vibration mechanism was analysed using Gaussian software, after which a gradient moisture content insulating oil sample was prepared and tested using the built terahertz platform. Theoretical analysis and experimental results show that: 2.27THz is the vibration frequency of moisture in insulating oil system, the amplitude of 2.27THz characteristic peak is linearly related to the moisture content (R2>0.95), which can be combined with the results of terahertz absorption spectroscopy test inversion of the insulating oil moisture, to realize the rapid non-destructive evaluation of moisture.

Epistemic and aleatory uncertainties pose significant challenges in evaluating distributed generation (DG) hosting capacity (DGHC). To address these uncertainties simultaneously, this paper introduces a robust analysis approach integrated with information gap decision theory (IGDT) for DGHC evaluation in multi-distribution lines interconnected by SOPs. Firstly, leveraging the hyperspace-based method, the robust hosting capacity (RHC) for a radial line is extended to the robust hosting region (RHR) for multiple lines. The robust-IGDT model is then enhanced to support RHR evaluation in interconnected lines. An effective solution procedure is convert the proposed model into a mixed integer second-order cone programming (MISOCP) model. Numerical results validate the necessity of the optimization model for RHR, the interaction of DGHC in interconnected lines, and the effectiveness of the proposed transformation method for solving the nonlinear robust-IGDT model.

The wide integration of distributed generation (DG) imposes a huge influence on distribution network (DN) and even leads to the risk of thermal overload and voltage violation. Therefore, it is significant to evaluate DG hosting capacity and judge the feasibility of all DG integrated requests. First, this paper proposes the definition of robust location for DG hosting capacity, especially when soft open points (SOPs) and distribution network reconfiguration are considered. All DG integrated requests are allowable if the sum of them do not exceed DG hosting capacity in robust location. Then, a Wasserstein distributionally robust optimization (WDRO) model with chance constraint is formulated to evaluate DG hosting capacity in DN with SOPs. Meanwhile, a systematic solution procedure is developed for the proposed nonlinear optimization model. Numerical results authenticate the effectiveness of WDRO with chance constraint and effects of SOPs and network reconfiguration to improve DG hosting capacity.

With the increasing global dependence on renewable energy, the importance of photovoltaic power generation as a clean and renewable form of energy is becoming increasingly prominent. Photovoltaic inverters, as the core equipment of photovoltaic power generation systems, are not only responsible for converting direct current into alternating current, but also play a crucial role in power quality management and grid support. This article aims to explore the application of photovoltaic inverters in the governance of power grid quality, analyze their grid support functions, and provide prospects for future development.

With the increasing global emphasis on sustainable development and environmental protection, the green credit evaluation of power grid suppliers has become an important indicator to measure their environmental performance. However, in actual datasets, the presence of outliers may seriously affect the accuracy and reliability of credit evaluations. This article proposes outlier identification in green credit data of power grid suppliers based on Markov Chain Monte Carlo (MCMC) algorithm. Firstly, the imbalanced data is preprocessed through data cleaning, data standardization, and data balancing. Then, the MCMC algorithm is introduced, which utilizes its powerful probability sampling and parameter estimation capabilities to effectively identify and handle outliers in green credit data. By constructing appropriate statistical models, the MCMC algorithm can iteratively explore the data space and accurately identify potential outliers. The experimental results show that this method can not only improve the quality and accuracy of data, but also enhance the accuracy of outlier identification, demonstrating significant advantages in promoting green behavior of power grid suppliers, and providing strong support for building a more fair and transparent green credit evaluation system.

In order to promote the consumption of renewable energy into new power systems and maximize the complementary benefits of wind power (WP), photovoltaic (PV), and energy storage (ES), studying a collaborative planning of wind, PV and energy storage systems is of significant importance. This paper first considers the seasonality, uncertainty, and correlation of WP and PV outputs, generating joint output scenarios reflecting the correlation between WP and PV power based on Copula functions. These scenarios are reduced to typical operating scenarios using the simultaneous backward reduction (SBR) algorithm. Secondly, a multi-objective planning model is established, considering both the economy and the environmental sustainability of the system. The model is converted into a single-objective problem using the analytic hierarchy process (AHP), and a carbon reduction benefit evaluation index is established. Finally, a case study of a power supply area in Wenzhou was conducted to validate the effectiveness of the proposed planning method. Compared to planning models that do not consider wind and PV power correlation, the proposed planning method reduces the system's annual investment and operating costs by 90.56527 million yuan, increases carbon reduction benefits by 89.79 thousand tons, and improves the annual renewable energy absorption rate by 0.64%.

With the continuous development of the new power system, accurately predicting the total electricity consumption has become increasingly important. This paper proposes a daily electricity consumption forecasting method based on multi-type electricity consumption decomposition. First, the total electricity consumption is divided into base electricity consumption and temperature-controlled electricity consumption. The base electricity consumption is predicted by fitting it with economic indicators that show high Pearson correlation coefficients. Then, a genetic algorithm is used to optimize eXtreme Gradient Boosting parameters for accurately forecasting the rapidly changing temperature-controlled electricity consumption. Finally, the results of both predictions are linearly combined to obtain the total forecasted electricity consumption. Simulation results shows that the proposed method effectively predicts the daily electricity consumption for a provincial power grid in China, validating its effectiveness.

This article studies the electrical protection technology requirements for the use of shore power by docked ships to ensure the safe and stable operation of the ship's shore power system in complex environments. By exploring the design and control strategies of electrical protection systems, the aim is to reduce equipment failure rates, eliminate safety hazards, improve energy efficiency, and support the development of green ports and low-carbon shipping. Detailed analysis of the three-level protection mechanism of shore power systems, analysis of the causes and countermeasures of short-circuit faults at different nodes, calculation and simulation of short-circuit currents for various types of shore power systems, analysis of the characteristics of short-circuit current changes, providing an analytical method for the rational configuration of circuit breakers, and emphasizing the importance of scientifically setting the protection system setting values.

An active distribution network (ADN) planning and design architecture was developed. The content requirements of AND planning were given from the aspects of power grid status, load forecasting and power balance. Based on the probabilistic output interval of distributed generation, the formulation method of network load coordination plan was studied. Finally, the electrical calibration method of AND was presented to verify the reasonableness of the formulation of the plan.

Due to the special operating environment of the cable, it is very easy to be affected by external factors in the operation process, the formation of local defects, affecting the safe operation of the power system, so the accurate detection of cable defects in the area of the maintenance of the power system security and stability is of great significance. The first step to achieve cable detection is to obtain the broadband impedance spectrum of the first end of the cable, in order to overcome the current acquisition of the impedance spectrum of the equipment is expensive and not easy to carry and so on, this paper proposes a method based on the amplitude-angle transform to generate the impedance spectrum, improve the performance of the anti-noise and reduce the cost of the instrument.

Due to the complex operating environment of distribution network cables and the stringent requirements for outage maintenance, there is an urgent need for accurate and effective new live detection technologies. This study focuses on the induced current in the metal shielding layer of a 10kV single-core cable. Through theoretical derivation and modeling simulation, the evolution patterns, inherent mechanisms, and influencing factors of harmonic distortion in the induced current were investigated. The simulation results indicate that magnetic field distortions at the insulation defect locations cause abnormal harmonic components, specifically the 3rd, 5th, and 7th harmonics, in the induced current within the metal shielding layer. Further real-world experiments show that the main components of these harmonics are closely related to factors such as load current, the type of insulation defect, and the through-flow aging time of the insulation material. Finally, by applying the K-means clustering analysis algorithm to the measured harmonic data, effective classification of insulation defects in distribution network cables was achieved. At a conductor current of 400A, the recognition rate for water droplet defects reached 84.5%, providing a theoretical basis for timely warning and live diagnosis of insulation defects.

Suspended water droplets is currently an oil-immersed transformer internal insulation discharge, breakdown of an important reason, this paper builds a simulation of the transformer test platform, the test by changing the flow rate of 0~1.8m³/h, the temperature of 40~70°C each of the four variables to study the law of change of the oil suspended droplets of partial discharge (PD), according to the skewness, the steepness, the number of peaks and the localization of the maximum discharge with the flow rate, temperature changes to determine the coupling relationship of PD. The coupling relationship of PD is judged according to the change of skewness, steepness, number of local peaks and maximum discharge with the change of flow rate and temperature. The test results show that the larger the flow rate is at constant temperature, the more unstable the PD of suspended water droplets is, and the overall trend of discharge is decreasing; when the flow rate is constant, the water droplets are mostly in the dissolved state at 50°C, and the electrical discharge decreases, and the thermal movement of molecules increases at 60,70°C, and the electrical discharge increases, and the number of the phase points of the electrical discharge shows a decreasing and then an increasing trend.

Electronic transformer was an important device for the intelligent development of substation, and its insulation performance was highly required due to working in a multi-physical field coupling environment. This study proposed an experimental method for the insulation performance of coupling decoupling network (CDN) under temperature-humidity coupling environment, and designed and developed the corresponding test device and host computer software, and finally tested and verified it with four different insulating materials, namely, acrylic, silica gel, paraformaldehyde and polyurethane. Different temperature and humidity conditions were simulated in the test device, and a DC high-voltage generator was used to conduct voltage withstand tests to measure the voltage withstand capability of different materials in the temperature and humidity coupling field. The results showed that there was a significant difference in the performance of different insulating materials in the temperature and humidity coupling environment. Under the same temperature and humidity conditions, acrylic had a higher voltage resistance.

Distribution network’s line break is a typical fault type of distribution network. Generally speaking, line breakage faults can occur at any position of the line, which can be roughly divided into power supply side, middle section, and load side. Generally speaking, after a single-phase line break occurs, the relative ground voltage of the line break phase increases, while the two-phase voltage of the phase without line break decreases. However, the location of the line break point is closer to the power side or the load side, and the voltage changes between the fault phase and the non fault phase are not exactly the same. This paper analyzes the principle of neutral point voltage displacement and voltage asymmetry caused by single-phase line break in power distribution system with neutral non-effectively grounded through formula derivation. Finally, a typical case is analyzed to investigate the voltage offset caused by single-phase line break.

In high-altitude regions with high wind speeds, irregular wind-induced ice shedding on OPGW (Optical Ground Wire) severely affects the normal operation of power systems. Addressing the impact of typical crescent-shaped ice cover on OPGW wind load body shape factors, this paper employs computational fluid dynamics to simulate the airflow around the conductors. Numerical simulations are used to calculate how the aerodynamic coefficients vary with wind attack angles under different wind speeds and ice thickness conditions. The results indicate that increasing ice thickness does not alter the trend of aerodynamic coefficient variations but significantly affects their values. The aerodynamic coefficient initially increases and then decreases with the wind attack angle, reaching maximum values at 90° wind attack angle when the windward area is largest.

In the traditional short-circuit fault characterization of transmission lines of new-type power systems, one end is equivalent as the traditional AC system dominated by synchronous generators, while the other end is the new energy field station connected. The short-circuit fault characterization in this scenario can provide support for the research and test verification of new principles of longitudinal differential protection, distance protection and current protection for new energy-connected distribution lines or transmission lines. However, in the context of large-scale new energy plants coming into operation on the transmission grid system side, both sides of the new power system lines in some regions will be dominated by new energy sources, with weak feeder characteristics at both ends. Taking this as the background of the study, we analyze the short-circuit fault characteristics by taking into account the low-voltage ride-through (LVRT) strategy and the system short-circuit ratio (SCR) index of the new energy stations, build the corresponding distribution network model, and give the short-circuit fault characteristics of some typical fault scenarios, which points out the future challenges of the new type of power system line fault analysis, relay protection, and fault localization.

Ice shedding from heavily iced transmission lines frequently causes significant vertical vibration responses, which may result in damage to transmission structures and line flashovers. Most existing research on conductor jump behavior after ice shedding focuses predominantly on ice shedding events alone, without considering the influence of wind during the shedding process. This paper introduces a finite element approach to assess the dynamic behavior of transmission conductors under the combined effects of wind and ice-shedding. A typical iced two-bundled conductor with ice bridges serves as the subject for this study, and the finite element method is utilized to model the jump height of the conductor under these combined forces. Furthermore, a parametric study examines the influence of critical variables such as wind speed, attack angle of wind, and the rate of ice shedding on the jump height of heavily iced conductors under the interaction of wind and ice-shedding. This research offers valuable insights for the design of transmission lines in regions prone to heavy icing.

Propylene carbonate (PC)-based electrolytes offer significant advantages for low-temperature discharge, but their performance at extreme ion concentrations is not yet well understood. This study explores the molecular-level differences in solvation shell structures of PC and ethylene carbonate (EMC) mixed electrolytes at extreme LiPF₆ concentrations under low-temperature conditions (253.15K), and analyzes the transport properties of diffusion coefficients and electrolyte conductivity. The study finds that with increasing LiPF₆ concentration, the number of PC molecules in the solvation shell decreases, while the number of PF₆̅ ions increases, leading to a rise in conductivity. When the LiPF₆ concentration exceeds 1M, the increment of PF₆̅ involved in the solvation structure diminishes, and the rate of increase in conductivity gradually slows down. This indicates that at high concentrations, more PF₆̅ ions participate in the formation of solvation structures, which contributes to the enhancement of conductivity. This research provides a design basis for the application of PC-based electrolytes in low-temperature fast-charging batteries.

In this paper, coal asphaltene/polyacrylonitrile based nitrogen doped porous carbon membrane (NPCM) was prepared by electrospinning using SBA-15 as hard template agent. The effects of raw material composition and carbonization temperature on the carbonization yield, specific surface area and capacitive properties of the porous carbon membrane were studied. When the mass ratio of SBA-15:asphaltene:polyacrylonitrile=1:1.2:4.8, the carbonization yield (58.7%) and specific surface area (427.6m²/g) of NPCM2 were higher. The specific capacitance of NPCM2 reaches 214.2F/g. After 10000 times of charge and discharge at 1A/g, the capacitance retention rate of NPCM2 can reach 94.1%. Coal asphaltene/polyacrylonitrile based nitrogen doped porous carbon membrane is expected to become a high-performance flexible electrode material.

Ultra-high frequency (UHF) method of partial discharge detection has the advantages of high sensitivity and high signal-to-noise ratio, the existing external transformer sensors have low sensitivity, while the built-in sensors will affect the actual operation of the transformer, which limits the application of UHF sensors in the field partial discharge detection of transformers. For this purpose, it is proposed that the transformer core be employed as an UHF antenna for the purpose of detecting the electromagnetic signals generated by partial discharges. Three distinct transformer core configurations are selected for use as UHF antennas, and their respective models are developed and subjected to simulation. The antenna characteristic parameters of the core are simulated and calculated, and the results show that the core can be used as an antenna for partial discharge detection in the UHF range. The entire transformer is modeled, and the receiving characteristics of the core inside the transformer for UHF signals are simulated. The simulation results show that the iron core can sense the UHF signals generated by partial discharges well and play the role of detecting partial discharges.

This paper analyzes the Small Modular Reactor (SMR) nuclear power plant low-voltage power cables in different application environments of the baseline current-carrying capacity determination, current-carrying capacity correction, cable cross-section selection, cable cross-section calibration of the principles and methods, as well as the use of standards. Focus on comparative analysis of low-voltage cables in the bridge randomly filled with laying to determine the method of load capacity, small piles according to the bridge filling rate is not the same, the allowable heat is not consistent, according to the different allowable heat determines a different cross-section of the cable in different filling rates under the load capacity, and the national standard is based on the number of layers of the cable to determine the load capacity correction coefficients, respectively, applicable to the different methods of laying. Finally, a flow chart gives the cable application environment to determine the cable cross-section selection and cable cross-section calibration of the process followed, for the subsequent nuclear power engineering design and improvement provides a reference.

With the development of modern industry and science and technology, the traditional monofilament diameter measuring technology has been unable to meet the measurement requirements of the high precision and wide applicable range. And the ultra-high precision filament measuring instrument is very harsh to its working conditions. Therefore, it is of great theoretical and engineering significance to develop a high-precision, wide-measuring range and fast-measured wire diameter measurement system that can be used in actual industrial production. With the rapid development of optoelectronic science and technology and signal processing technology, charge-coupled devices (CCD) and digital signal processing technology have been widely used in the field of non-contact diameter measurement. This paper is based on projection imaging technology to magnify the filament projection to the linear CCD photosensitive surface Sensing the photoelectric signal, collecting the signal through the embedded system, and finally using the mean filtering, wavelet noise reduction and quadratic curve fitting technology to optimize the measured signal, so as to realize the fast and efficient measurement of the diameter of the filament.

Rechargeability improvement Zn-MnO₂ battery is crucial to the further development and wide application of this battery. This work demonstrated, conventional Bi₂O₃ doping by physical method into γ-MnO₂ as a cathode, PVA-KOH alkaline gel polymer electrolyte (GPE) as an electrolyte, and zinc powder as an anode. The assembled solid-state Zn|GPE|MnO₂-Bi₂O₃ cell presents certain rechargeability, at the 77% discharge depth of MnO₂ one-electron discharge capacity and a cut-off voltage of 0.7V. Discharge capacity kept over 55% of the first discharge capacity even at the 20^th cycle. The improvement of rechargeability is attributed to the enhancement of electrochemical reversibility of MnO₂ modified by Bi₂O₃.

In this paper, the welding techniques for brackets and rings of grading rings used on UHV transmission lines in high altitude areas are optimized, and four new welding methods, including strengthening the surface of ring welding, single side drilling of ring welding, bending welding of bracket and combination welding, were proposed. The conventional welding method was used as the control group to carry out tensile and torsion tests. According to the test results, the two welding techniques essentially produce the same results as the conventional welding technique when the specimens are in their tensile state. The technique of punching on one side of the ring significantly outperforms the conventional welding technique when the specimens are in their torsion state. The technique of welding a reinforced surface on the ring has a less favorable effect than the conventional welding technique because of the increased welding area and consequently, a larger heat-affected zone. The test results indicate that the technique of punching on one side of the ring is advised for grading rings used in high altitude and thick ice cover areas.

As a key and core component of energy storage system, the safety and reliability of lithium-ion battery directly affect the comprehensive performance of energy storage system to a large extent. Aiming at the safety problem of energy storage batteries, a method for predicting the health state (SOH) of lithium batteries based on improved autoregressive recurrent neural network (DeepAR) was proposed. Firstly, the characteristic information such as capacity, internal resistance and time interval are extracted from the operating data of lithium batteries, and the features with strong correlation with battery health status are found through correlation analysis method as the input of health factors. Then, residual connections are introduced into the DeepAR model to reduce gradient disappearance during training, and the adaptive Dropout regularization method is used to improve the generalization ability of the model. Finally, the data set of lithium battery from University of Maryland is used to verify the validity of the model. The experimental results show that the maximum root mean square error (RMSE) is less than 0.01, and the mean absolute error (MAE) is less than 0.011. This method has high accuracy for SOH prediction of lithium-ion battery, and has certain application value for safety research of energy storage battery.

Lime rotary kilns are widely used in the industrial calcination of quicklime. However, coal-fired rotary kilns, while ensuring output, also emit a large amount of NO_x, which causes significant environmental pollution. It is imperative to promote NO_x emission reduction in coal-fired rotary kilns. Based on the production parameters of a rotary kiln at an enterprise, a new low-NOx burner suitable for coal-fired rotary kilns was designed. The burner reduces NO_x emissions by enhancing air and fuel mixing to avoid localized high temperatures. The technical parameters and structural parameters of the burner have been calculated in detail. The design dimensions of the primary coal grinding channel, central air channel, secondary coal grinding channel, swirling air channel, and axial air channel are 108*4mm, 133*4mm, 219*5mm, 345*6.5mm, and 325*7mm, respectively. This work provides theoretical guidance for the processing and use of low-NO_x burners.

This study simulated water content and temperature distribution in a PEMFC with parallel and cooling channels. Key findings indicate that co-directional inlet flow enhances performance with higher current density and uniform temperature distribution. Increased operating pressure boosts current and temperature, while higher humidity decreases current due to flooding risks and slightly raises temperature. Optimizing pressure and humidity is crucial for balancing performance and thermal management. Future work should refine flow channel designs and validate simulations experimentally for better PEMFC application.

In the realm of electrical energy metering, the accuracy and reliability of current transformers (CTs) and potential transformers (PTs), collectively referred to as instrument transformers, are paramount to safeguarding the economic interests of power suppliers, transmitters, and consumers. Traditionally, post-installation verification of these transformers' error rates necessitates system downtime, which poses significant operational challenges. To address this issue, this paper introduces a novel analytical approach for evaluating the relative error deviations of a wide array of instrument transformers within a power grid. By conceptualizing transmission lines as passive two-terminal networks, and leveraging the inherent stability of transformer errors over short periods, the method employs partial derivatives to determine the sensitivity of transformer error coefficients to variations in line parameters. Furthermore, the methodology proposes the selection of a specific transformer segment as a reference standard, enabling the calculation of relative error magnitudes for transformers located at substations across the line. The validity of the model was substantiated through ATP (Alternative Transients Program) simulations, which demonstrated its capability to predict the relative error deviations of instrument transformers across a broad geographical scope.

This research employed hot pressing sintering technology to explore the impact of varying sintering temperatures on the synthesis and electrical characteristics of tetrahedrite, under preparation conditions spanning 400 to 550°C. The phase composition and microstructure of the tetrahedrite were ascertained through X-ray diffraction (XRD) and scanning electron microscopy (SEM) analyses. The findings revealed that within the sintering temperature range of 450 to 500°C, the synthesized samples displayed a uniform phase structure comprising Cu₁₂Sb₄S₁₃ and Cu₁₄Sb₄S₁₃. Through the measurement of the Seebeck coefficient and resistivity, the trend in the electrical properties of the samples was delineated. Notably, at a sintering temperature of 500°C, the sample achieved a peak power factor of 104.07μW·(m·K²)^-1.

In response to the problems of long training time and poor classification performance of Convolutional Neural Network (CNN) in small sample bearing fault diagnosis, this paper proposes a diagnostic model based on S-transform and CNN-SVM. Firstly, the bearing vibration acceleration signal is transformed into a time-frequency image through S-transform (ST), and CNN is used to extract features from the ST time-frequency image to obtain deep features. Then, after regularizing these deep features, they are input into Support Vector Machine (SVM) for feature classification, fully utilizing the model's classification ability and improving the accuracy of bearing fault classification. The experiment shows that this method still has good diagnostic performance under small sample signals and noisy conditions. Compared with other methods, it has better noise resistance stability and stronger generalization ability.

A new type of "jacket type" cooling channel was designed in order to improve the efficiency of a fuel cell, which is crucial for regulating its temperature. The choice of cooling channel structure significantly impacts the operational performance of the fuel cell. The results of the study indicate that among the two cooling channels investigated, the serpentine pipe cooling channel exhibited superior cooling performance. Specifically, it managed to reduce the maximum temperature of the battery from 388K to 333.45K under similar cooling conditions. Additionally, the current density generated by the serpentine flow channel was found to be 10% higher compared to that of the parallel flow channel. Consequently, selecting the appropriate cooling channel structure is essential for optimizing the operational efficiency and performance of fuel cells.

With the booming progress of offshore oil and gas development into the deep sea, the internal conditions of submarine pipelines are becoming more severe, and especially in CO₂ medium, the pipeline weldment is faced with severe non-uniform corrosion risks. In this paper, two welding processes of AWS E9015-G/ER80S-Ni1 and AWS E6010 are used to weld X65 pipeline steel respectively, and the heterogeneous areas are sliced and processed respectively. Furthermore, a multi-ring electrical resistance sensor array is established, which can realize the simultaneous online monitoring of the corrosion difference between heterogeneous welding areas and the corrosion difference within the circumferential homogeneous region. Through the non-uniform corrosion depth monitoring and corrosion morphology characterization, it is shown that the FeCO₃ corrosion product film can increase the potential of the film-covered area. At the same time, the microstructure with irregular size and uneven distribution will reduce the corrosion resistance of the welding area, while the uniformly distributed "pearlite/ferrite" microstructure facilitates the development of a compact and complete FeCO₃ as a corrosion product film. Furthermore, in the welding area with earlier film formation and better density, the polarity of the galvanic current could be changed.

DC current intrusion into the transformer makes the transformer magnetic density working point shift, generating DC bias magnetism, which jeopardizes the safe operation of the power system. In order to achieve this, firstly, the mechanism of DC bias generation is analyzed and a simulation model of DC bias current is established, secondly, a DC bias calculation model is constructed in Xinjiang based on the measured soil resistivity and AC grid structure, and the influencing factors of DC bias current are quantitatively analyzed, and lastly, the influence of the DC bias current on transformer DC resistance and transformer DC resistance is investigated and analyzed in order to provide a better solution for the safe operation of power system. Finally, by comparing and analyzing the calculation results, the influence of different earth resistivity, grounding pole distance and transformer DC resistance on DC bias current is obtained, which provides some guidance for the prevention of DC bias in existing substations and substations in the planning period.

In order to maximize the utilization rate as well as the economy of the Blocking Device for suppressing the DC Bias of the transformer, it is necessary to conduct a study on the optimal arrangement of the Blocking Device for substations in the region. Firstly, the DC Bias current distribution within the AC grid is obtained by calculating based on the field-circuit combination model. Secondly, by using the ACO (artificial ant colony algorithm), it can reduce the input cost of the Blocking Device as much as possible while the transformer is safe, so as to achieve the best blocking effect with the minimum number of Blocking Devices. Finally, an actual topology model based on a region in Northwest China is established for verification, and the results show that the proposed algorithm can effectively suppress the risk of DC Bias.

Methane plays a crucial role in deep-sea cold seeps, hydrothermal ecosystems, Earth's carbon cycle, atmospheric greenhouse effects, and the formation of hydrates. In-situ methane sensors can provide real-time online monitoring of methane concentrations in deep-sea environments. The response time of these sensors is a critical parameter for evaluating their real-time performance. Based on the structure of a self-developed membrane degassing in-situ methane sensor, a gas-liquid dynamic equilibrium response model was established using gas diffusion and dual-membrane exchange theories. The study found that the response equation for deep-sea in-situ methane sensors follows a natural logarithm function. The response time improves with larger membrane areas and smaller internal flow field volumes. Experimental evaluation of the sensor's response performance showed results consistent with the theoretical model, with a measured response time t_0.63 of 30 minutes. This provides valuable insights for structural optimization and performance enhancement of methane sensors.

Aiming at the problems of low accuracy and high detection cost of Potential Transformer (PT) state online identification methods, a potential transformers state assessment technique with wide-area measurement is proposed. Experimental results show that the accuracy of the results of this paper's method on the data set is 94%, which can meet the accuracy requirements of PT metering error state assessment.

The hydraulic, mechanical and electrical factors are coupled with each other during the operation of the hydroelectric generating set, which is highly nonlinear, unstable and time-varying, and it is difficult to accurately model and predict. Aiming at the problem of hydraulic turbine generator failure prediction, this paper attempts to introduce convolution (Conv), integrate long short-term memory neural network (Long Short Term Memory, LSTM), and propose a Conv-LSTM deep learning prediction network. At the same time, in order to solve the problem of hyperparameter optimization, the chaotic firefly algorithm (CFA) was introduced, and a fault prediction method for hydro turbine generator sets based on CFA-Conv-LSTM was constructed. Using the measured data of No. 1 unit of a hydropower station in Guangxi, compared with other commonly used methods, it is proved that the method is significantly better than other methods in terms of fault prediction accuracy and process monitoring performance, and has good application prospects and promotion value.

Flexible sensing technology has wide applications in smart manufacturing and robotic artificial intelligence. Sensitivity is a crucial parameter for evaluating sensors. However, research on the impact of geometric dimensions of porous flexible sensors on sensitivity remains insufficient. In this study, we investigate the effect of dielectric layer height and electrode size on the sensitivity of porous flexible capacitive pressure sensors using the finite element method. Our results indicate that decreasing the dielectric layer height and increasing the electrode area leads to higher sensitivity.

Sensors utilizing friction nanopower generation possess the ability to directly transform external stimuli into electrical signals. This allows for the assessment of external stimuli based on variations in these electrical signals, thereby facilitating self-powered sensing. Notably, the integration of rigid-flexible coupling technology in tactile sensors addresses the viscoelastic limitations inherent to traditional flexible tactile sensors. The development of an ultra-sensitive triboelectric tactile sensor, which combines a hybrid force transfer layer of rigid and soft materials with a compliant bottom friction layer, is suitable for dynamic force detection. Experimental results demonstrate that the sensor possesses a high sensitivity of 1240mV/kPa and a broad force detection range from 0.1 to 1500kPa. Furthermore, this tactile sensor can discern multiple force directions, offering significant promise for applications in wearable sensing.

SF₆ circuit breakers are widely used in power system. Due to the accumulation of arc ablative effect, the arc contact state of SF₆ circuit breakers deteriorates continuously, which will lead to the decline of the insulation grade and breaking capacity of the break chamber. The dynamic capacitance simulation model of SF₆ circuit breaker was established, and the dynamic capacitance influencing factors were studied. Simulation study of the static arc contact length, static arc contact ablation angle, dynamic arc contact inner diameter and arc contact surface fluoride on the dynamic capacitance characteristics. The establishment of a comprehensive consideration of deterioration caused by various changes in the contact simulation model and test results for comparison, the results show that with the increase in the degree of comprehensive deterioration, the dynamic capacitance curve just split point travel down, just split point capacitance rise, completely split point capacitance is unchanged, the rule of change and the test results are consistent with the validity of the contact deterioration model.

In the construction of large diameter rescue wells, a lot of tripping operations are needed for drill pipes, drill collars and other drilling tools. Aim at that frequent screwing and unscrew of the top drive active drill pipe and the drill string in the tripping operation of the traditional drilling machine, the operation efficiency is low, the labor intensity is high, and the buckle is easy to be damaged. The rapid connection method of drill pipe suitable for conventional drilling tools is studied, and the hydraulic lifting device for rapid drilling under the flag is designed. The maximum lifting force reaches 1350kN, during the tripping operation, the hydraulic lifting device directly grabs the drill rod to realize the rapid connection between the power head and the drill rod; at the same time, it combines with the electro-hydraulic remote control system to complete the remote control of the drill pipe tripping operation. Finally, a set of tiltable hydraulic lifting device suitable for rapid tripping of large diameter rescue wells is formed. Through structural mechanics analysis, performance test and field industrial application, the average tripping efficiency of the hydraulic lifting device is up to 3 minutes/piece. And that trip efficiency is improved. And equipment support is provide for rapid construction of that rescue well.

In view of the fact that temperature rise, load and no-load testing are needed for most of the traditional efficiency testing methods of three-phase asynchronous motors, and torque measuring devices are difficult to be installed in the actual operation site, an online efficiency monitoring method based on air gap torque method is proposed, which has guiding significance for on-site measurement and evaluation of the operational efficiency of three-phase asynchronous motors.

Voltage source converter-based energy storage system (ESS-VSC) participates in power system frequency regulation actively. In this paper categorizes the stability characterization of ESS-VSC into external and internal characteristics, and establishes the impedance model of ESS-VSC to analyze the stability impacts causing by the increasing number of parallel ESS-VSCs. In addition, the transfer function of parallel ESS-VSCs is developed to analyze its frequency response stability caused by virtual inertia and damping parameter with the Bode diagram. Finally, a simulation model is developed using Matlab/Simulink platform to validate the accuracy of the simulation analysis.

To investigate on the flow field characteristics of a box-type bag filter device during the whole life cycle. This study established a CFD numerical calculation model of the dust collector device and verified the effectiveness in combination with the experimental results. Subsequently, numerical analysis was conducted under the consideration of the dust accumulation degree and the processing air volume. The study shows that with the increase of operating time, the dust accumulation degree on the filter bag increases, the surface permeability coefficient decreases, and it can be expressed as a negative exponential function of the operating time. As the dust accumulation degree increases, the uniformity of flow field distribution decreases, and the root mean square error of the device increases, while the increase in the processing air volume has no significant effect on the flow field. The total pressure drop of the device is mainly composed of the viscous resistance term caused and the inertial resistance term. The viscous resistance term is inversely proportional to the surface permeability coefficient and is proportional to processing air volume, while the inertial resistance term is proportional to the square of the processing air volume. Based on the numerical analysis results, this study established a empirical formula to describe the relationship between the pressure drop, filter bag resistance and processing air volume.

In recent years, the increasing requirements for energy conservation and emission reduction by the country, as well as the continuous operation of high-efficiency and low consumption new energy points, have made the operating situation of coal-fired power plants increasingly severe. While new energy such as wind power and photovoltaics continue to develop rapidly, how to absorb new energy generation has become a key factor restricting the development of new energy. Actively carrying out flexibility transformation of coal-fired power units to improve their adaptability and regulation capabilities is an inevitable choice for the development of coal-fired power units. In order to improve the heating reliability of the unit and enhance the comprehensive energy supply transformation and development capability of the enterprise, this article proposes a technical solution for a power plant in Shanxi Province that combines electric boiler decoupling technology and thermal storage tank decoupling technology. After analysis, the solution can meet the maximum heating demand during the heating period and has good economic benefits. It provides a new solution for power plants in China to achieve heating transformation in deep peak shaving environments, and has high practicality and promotion value.

In response to early characteristic signals are not obvious and easily affected by other signals such as noise, which makes it difficult to effectively extract characteristic components when motor is in mildly abnormal conditions such as broken rotor bars and rotor eccentricity, this paper proposed an early health diagnosis method of amplifying abnormal vibration characteristic signals using base screw loosening. Comparative study of radial electromagnetic force at air-gap under three cases of normal operation, rotor eccentricity and broken rotor bars reveals that the slight change in electromagnetic force features in rotor eccentricity is the main reason why vibration features are difficult to be extracted. The vibration response of motor housing is simulated for three cases under the base screw fixed and the base screw loose. Comparing the simulation results, it is found that the rotor eccentricity case can be effectively highlighted vibration features by the proposed method, thus carrying out more early and accurate health diagnosis of abnormal state, and providing a new idea for online early motor health diagnosis.

The prediction of the remaining useful life (RUL) of proton exchange membrane fuel cells (PEMFC) is one of the reasons limiting their large-scale application, and is a key focus of current researchers. Time series prediction methods for PEMFCs based on sliding windows, such as CNN and LSTM, have larger errors as the longer the time series prediction. To address the issue of error accumulation in the RUL prediction of PEMFC using traditional time series methods, this paper innovatively introduces the Informer model into the RUL prediction of PEMFC. Informer builds upon the Transformer architecture by incorporating a self-attention mechanism to mitigate the accumulation of prediction errors and improve the prediction effect of the model. By comparing the predictive results of the static and semi-dynamic PEMFC datasets with those of the traditional LSTM, it is verified that the Informer model has excellent performance in PEMFC time series prediction. The predictive results indicate that the Informer can significantly improve the accuracy of the RUL prediction of PEMFC to a certain extent.

It is very important to estimate the seismic performance of UHV (ultra high voltage) converter valve scientifically and rationally for the seismic safety protection of converter station. However, it presents a challenge due to the structural complexity of UHV converter valve. There is also a lack of research on the interaction between the valve and other important interconnection equipment, which leads to inadequate seismic risk assessment of the UHV valve. For considering the connecting interaction between UHV converter valve and bushing of converter transformer in valve side, the finite element model of the overall system of valve-valve hall-converter transformer is established. The main seismic vulnerability indicators of UHV converter valve are analyzed, including stress of suspension insulator, the relative displacement between converter valve inlet/outlet position and converter transformer bushing, and displacement in the bottom of the valve. It provides the reference and suggestion for the research on seismic safety protection technology of the converter valve in UHVDC (ultra high voltage direct current) power transmission project.

Aiming at the problem that the existing single-column wind power platform cannot work normally under the extreme sea conditions of strong typhoons, a VX type semi-submersible platform is proposed. The hydrodynamic finite element model of the platform is established by using AQWA software. The frequency domain and time domain calculation are carried out based on the three-dimensional potential flow theory, and the combined effects of wind, wave and current load are considered. The hydrodynamic analysis of the floating platform structure and the overall structural strength analysis are carried out under four working conditions, typhoon, towing and maintenance. ANSYS/Fatigue software is used to analyze the fatigue damage at the hot spot of the platform under working conditions, and the fatigue life is calculated according to S-N curve. The results show that the overall strength of the VX semi-submersible platform under various working conditions can meet the requirements of the specification, and the overall life of the platform can meet the design life of more than 25 years.

Due to its unique phase transition properties, vanadium dioxide (VO₂) has attracted significant attention in smart window applications. However, VO₂ currently has some shortcomings in the phase transition field, mainly including the uncontrollability of the phase transition process, insufficient crystallinity, and weak bond strength. Therefore, this study prepared M-phase VO₂ with high crystallinity through annealing treatment, significantly enhancing the bond strength between vanadium and oxygen atoms, thus improving the material's stability. This enhanced stability reduces energy barriers during the phase transition, making the transition more controllable and reversible. The prepared VO₂(M) exhibits a distinct endothermic peak at 67.40°C, with a peak heat flow of 0.59W/g. The results indicate that M-phase VO₂ prepared through simple annealing treatment is highly suitable for applications requiring efficient phase change materials, overcoming the shortcomings of traditional VO₂ materials in the phase transition field.

This paper examines the insulation risks associated with metallic particles within the mechanism chamber of high-voltage tank circuit breakers. An experimental platform was designed to analyze the discharge characteristics of metallic particles on the surface of horizontally oriented cylindrical insulating tubes subjected to impulse voltage. The results show that both the average amplitude and frequency of particle discharge increase with rising voltage. However, the average discharge amplitude tends to saturate or even decrease due to a rise in low-energy discharge events. Metallic particles positioned closer to the electrode exhibit higher discharge amplitudes and shorter discharge delays. A linear arrangement of particles increases their effective length, promoting discharge progression, while a parallel arrangement increases particle curvature, which suppresses discharge. Under positive polarity voltage, the discharge amplitude of particles near the high-voltage side is greater, and the delay is shorter compared to particles near the low-voltage side under negative polarity voltage.

This study focuses on the development and analysis of a four-stroke, direct-injection hydrogen internal combustion engine using the CONVERGE CFD software. The research refines the hydrogen-oxygen combustion mechanism by adjusting key kinetic parameters from the GRI 3.0 methane mechanism for enhanced accuracy. Detailed simulations investigate the effects of piston geometry, fuel injection timing, ignition energy, and timing on the engine's performance. Additionally, the study explores the impact of increased expansion ratios in conjunction with the Miller cycle on thermal efficiency. Results are validated through error analysis and grid independence checks, providing significant insights into optimizing hydrogen engines for improved efficiency and reduced emissions. These findings contribute to the advancement of sustainable hydrogen-fueled automotive technologies.

In view of the current problems of substation operation and maintenance, such as excessive workload, diversified tasks, low inspection efficiency, inadequate inspection, and defects in inspection data statistics, this work researches and designs substation intelligent perception and operation and maintenance methods based on intelligent technology to realize distributed recording of the operation status of each equipment by inspection system, intelligent data acquisition, and intelligent inspection of substation. At the same time, the on-site operation of personnel is more efficient and accurate supervision and guidance, and the substation management provides multi-scene decision support, and finally realizes the multi-directional intelligent management of the substation.

Prognostics and health management (PHM) is considered a critical method to extend the lifetime of the proton exchange membrane fuel cell (PEMFC) and reduce maintenance costs. The premise of PHM is to establish a reliable and general degradation index. Electrodes and membranes are components that mostly influence the degradation processes of PEMFC. Combining the two catalyst and membrane degradation indexes, this paper establishes a hybrid degradation index for estimating the PEMFC degradation state in different operating conditions. Firstly, membrane and catalyst degradation models are utilized to estimate a single degradation index. Then, the two normalized single degradation indexes are fused to construct a hybrid degradation index. The validity of the indexes is analyzed through experimental data. The hybrid degradation index is suitable for predicting the degradation state and estimating the remaining useful life (RUL) of PEMFC.

Accurately predicting voltage is crucial for ensuring the safety monitoring of energy storage battery systems in energy storage stations. However, the battery system, as a highly nonlinear and dynamically changing complex system, faces the issue of cumulative errors in long-term forecasting. To address the poor accuracy and stability of voltage prediction in long-term scenarios for energy storage batteries, this paper proposes a Long-Term Series Forecasting model based on the progressive sequence decomposition concept and Transformer. The model consists of an encoder-decoder structure based on the Transformer network, incorporating a progressive sequence decomposition module to extract high-dimensional features from multiple semantic perspectives. This approach enables the model to capture long-term stable trends in unknown correlated feature dimensions, thereby improving the final prediction accuracy. Additionally, an improved auto-correlation mechanism network block is designed in the network to enhance the model's perception of the similarity of time series at different time spans, thereby enhancing the stability of the model in long-term series forecasting scenarios. Furthermore, this paper optimizes features for lithium-ion energy storage battery voltage data, encoding sequence features, battery parameter features, and trend features in separate domains. By effectively aggregating the correlations of various parameters, the prediction performance of the lithium-ion energy storage battery voltage forecasting model is significantly improved. Experimental results demonstrate that the proposed method exhibits good prediction accuracy and stability for voltage changes in the next 24 hours, with an average absolute error of only 0.013 compared to the actual voltage values. Through extensive comparative experiments, our method surpasses other time series models in terms of providing state-of- the-art accuracy, effectively enhancing the stability of long-term voltage forecasting.

With the increasing demand of electricity and the high pollution emissions of fossil fuels, the utilization of renewable energy has gained increased attention. The utilization of renewable energy, characterized by intermittency and variability, shows a challenge with space-time mismatches between electricity supply and demand. Energy storage technology based on phase change material (PCM) serves as an effective technical pathway to address this issue. However, due to the long time of thermal storage process for PCM, numerical simulation based on Computational Fluid Dynamics (CFD) often facing issues such as high computational consumption and long calculation times. Therefore, to address this issue, a new predictive method based on artificial neural network (ANN) is proposed in this study. A 2D numerical model of a triplex tube heat exchanger (TTHX) has been established and validated with experiment. The melting characteristics of TTHX under different working conditions were analyzed. Moreover, an ANN model was established to used to fit the numerical results with a mean squared error (MSE) of 2.75×10^-10 and R-squared (R2) of 0.990, which is of great help for the fast prediction and the optimization of PCM melting process.

We analyze and optimize the construction method of polynomial form in power systems, which is used to construct Lyapunov functions using the Sum Of Squares (SOS) method to analyze transient stability of power systems. This construction method is based on variable substitution of trigonometric nonlinearities in polynomials, without the need to first calculate the polynomial containing the trigonometric nonlinearities, which means we can skip this step and simplify the workload. At the end of this article, the correctness of this method is demonstrated by comparing it with the results of Time domain analysis.

The control strategy of photovoltaic grid-connected inverters is crucial for improving power system stability and efficiency. In this paper, the voltage equations in the three-phase stationary coordinate system are established, and the Park coordinate transformation is performed on the equations. The instantaneous active power and instantaneous reactive power models injected into the grid by the inverter are obtained after the transformation. The article designs a rotating coordinate system based on grid voltage vector orientation, whereby precise control of the grid current injected into the inverter is achieved. At the same time, the PI controller parameters are optimised using the cuckoo search algorithm, and the dynamic response performance of the system is significantly improved. Finally, the effectiveness of the proposed control strategy is verified through simulation experiments, and it is demonstrated that the method can considerably enhance the support of the system to the grid operation scheduling.

The assembly accuracy of the guide rail is closely related to the distribution state of the preload force of the bolt group. Bolts have relaxation characteristics during service, and the distribution of preload force gradually changes over time, which in turn affects the assembly accuracy of the guide rail. This article focuses on the time-varying characteristics of the distribution of preload force in bolt groups under different factors. Firstly, the relationship between the deformation of guide rail assembly and the distribution of preload force was analyzed. Secondly, based on the combined time hardening model, the general law of the dispersion of bolt pre- tightening force evolution over time was analyzed. Finally, the time-varying law of the preload force dispersion of the bolt group was analyzed under different pitches, joint surface friction coefficients, and preload force loading times. The results show that the dispersion of surface node deformation on the guide rail is positively correlated with the dispersion of preload force; The dispersion of preload force gradually decreases with time, and the downward trend gradually becomes gentle; Secondly, as the pitch and friction coefficient increase, the initial preload dispersion gradually increases, and the corresponding dispersion also gradually increases at the same creep moment. However, the percentage of dispersion decay gradually decreases within the same time period; The number of times the bolt preload force is loaded follows the opposite pattern.

At present, the development of wind power at home and abroad is facing many technological innovations and challenges, and the trend of large-scale blade is inevitable, but its reliability cannot be guaranteed. In view of the fact that most of the service locations of wind turbines are in areas with heavy rainfall, a set of intelligent rain erosion system is designed to simulate natural rainfall, and the life of the leading edge coating of wind turbines is predicted based on the fatigue damage of rain erosion, so as to reduce the maintenance cost of wind turbines, improve unit safety and increase energy output.

A heterogeneous information network(HIN) is a type of graph that contains various types of nodes or edges. The purpose of representing a HIN is to use low-dimensional, dense vectors to capture high-dimensional graph data. Many practical applications can be modeled as heterogeneous networks. For example, in an e-commerce network, merchants of different brands and users can be represented as different types of nodes, while relationships such as purchasing and following can be represented as different types of edges. Representation learning on such networks is beneficial for the construction of recommendation systems. Currently, the main representation learning methods for heterogeneous networks are the random walk shallow models and neural network deep models. However, since the meta-path in these methods cannot represent complex structures, this paper focuses on a meta-structure-based heterogeneous network representation learning method. It controls the random walk using the meta-structure, obtains the sampled node sequence, and uses it as the input for the word embedding training model, finally obtaining the node embeddings. In this paper, the meta-structure is used to guide the random walk. According to experimental comparisons, this approach achieves a better representation of heterogeneous networks.

The growing wind and solar power capacities significantly decrease the carbon emission and offer a viable solution to both the energy crisis and climate change. Large fragility and instability are brought into power systems by their intrinsically unstable power characteristics. To mitigate these challenges, energy storage systems have emerged as a prevalent solution. But Different configurations and running modes of energy storage systems have impact on grid stability and investment. The traditional optimization algorithms for energy storage configuration also have difficulties in equation-solving capabilities. So this paper proposed a new optimization algorithm for energy storage system configuration. It gives the estimated optimal energy storage configuration and comprehensive revenue, considering the electricity tariffs, power utilization and curtailed load power. The influence of different wind and solar power capacity ratios is also studied, meanwhile the suggestions for energy storage design in various power applications are given.

The construction of regional electricity market in China is progressing steadily, but the research on regional reserve market in China is still lacking. Therefore, this paper first calculates the bidding prices of generators in reserve market based on the clearing results of the spot market, then establishes a clearing model for regional reserve market, and finally builds a joint spot-reserve clearing model incorporating the constraints of both spot market and reserve market. Based on actual data of a four-province region in China, this paper analyzes the prospects for building a regional reserve market and the potential of the joint spot-reserve clearing method. The results show that the establishment of the regional reserve market can alleviate the system's lack of reserves and reduce the system reserve cost. The joint clearing method can greatly improve the adequacy of system reserve capacity and reduce the total cost of the system.

In this paper, the finite element model was established for a multi-pass drawing of tungsten wire, and the process of tungsten wire multi-pass drawing is simulated and analyzed. The study focused on the influence of die parameters and multi-pass drawing parameters on the surface hardening of tungsten wire. Through an analysis of the impact of drawing process parameters on the surface hardening of tungsten wire, the theoretical basis for optimizing the drawing process and improving the surface quality of tungsten wire were discussed.

In recent years, with the continuous development of the energy industry and the progress of technology, the traditional business model has shown a decline, and the terminal power consumption market has ushered in a new business model. The purpose of this study is to explore a common emerging business model for end-use electricity consumption based on knowledge graph and analyze its feasibility and potential business value. Through an in-depth analysis of current power market trends, consumer demand, and the rapid growth of renewable energy, the study proposes a comprehensive business model framework. Using qualitative and quantitative research methods, the framework constructs entity extraction, recognition, and simulation deduction methods, and explores the adaptability and profitability potential of emerging business models in different market and regulatory environments through case studies, market research and economic analysis, and designs flexible and efficient business models that contribute to sustainable energy development and environmental protection. At the same time. Taking the terminal electricity consumption in rural areas of Gansu as an example, the business model with the highest number of users is the rural self built and self sold model, and the business model with the largest scale of electricity consumption is the rural user enterprise co-built model. The simulation case demonstrates the feasibility of the proposed method.

The rationality and accuracy of selecting grid operation modes are crucial for ensuring the safe and stable operation of power systems. With the increasing complexity of grid structure and the intermittency and uncertainty of new energy and flexible loads, the operation scenarios of the power system show significant temporal features. The current traditional scene clustering methods do not adequately consider temporal features, and the manual extraction of typical operation modes is highly subjective, which bring new challenges to the safe and stable operation of the power system. Therefore, this paper proposes an improved K-means++ algorithm for Gaussian mixture model (GMM) based on shapelet temporal features and combined weights. Firstly, the Shapelet algorithm is applied to extract the typical features of multidimensional time series variables. Secondly, the UMAP algorithm maps the complex high-dimensional features to a lower-dimensional space, achieving feature dimensionality reduction. And in order to fully consider the degree of difference and correlation of temporal features, the improved entropy weight method fused with the CRITIC weight method is used to assign the combined weights to temporal features. Finally, the weighted Gaussian mixture model (GMM) is used to improve the K-means++ algorithm for clustering the grid operation data of a province. The results of the algorithm show that compared with the traditional scene clustering method, the method in this paper can effectively extract complex temporal features, and has better performance in silhouette coefficient, DBI and CHI indexes. Moreover, the derived typical operation modes for the power grid prove to be highly illustrative and representative.

The air conditioning system of electric vehicles is crucial to ensure the comfort of passengers and reduce energy consumption. This paper establishes a multi-objective optimization co-simulation model of an electric vehicle air conditioning system based on AMEsim and HEEDS. With the system cooling capacity, compressor energy consumption, performance of coefficient, and temperature drop time as the optimization objectives and the evaporator outlet air temperature, operating pressure, and pressure ratio as the constraints, the NSGA-Ⅲ algorithm is used to select the system operating parameters that meet the optimization objectives and constraint conditions. The effects of different operating parameters on the optimization objectives are analyzed. The results show that the research method can effectively locate a reasonable range of different operating parameters, compressor speed is the most important factor affecting the optimization objectives, and parameter sensitivity analysis results help formulate more effective operation control strategies.

In order to analyze the reliability of the ultra-long distance relay pumping and filling system in the actual operation of Jisuo Coal Mine, a fault analysis was conducted on the key equipment of the system in conjunction with the filling process. With the filling system failure as the top event, a fault tree model was established with 13 intermediate events and 42 basic events. After qualitative and quantitative analyses of the fault tree model, the structural importance of the basic events was obtained. Based on the established fault tree model, Monte Carlo simulation analysis was conducted to determine the priority order of the importance of the 42 basic event modes. It was found that the crushing subsystem and the mixing subsystem have the greatest impact on the reliability of the filling system, with the most significant mechanical causes being the mixing drum getting stuck or unable to rotate and the drive motor being overloaded. By comparing actual data with calculation results, the accuracy and effectiveness of the analysis were verified.