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The flexible building energy storage coupling dispatching framework and optimal dispatching model have been established in this paper by using the multi-levels network dispatching analysis method of the grid system. It would include solving the optimization model with the objective function having the minimum standard deviation and the constraint conditions of charging and discharging power and capacity. Second, a simulation analysis who used an example is implemented based on the typical daily load of a Tianjin district. The findings indicate that: energy storage, construction, and flexible energy use The joint optimization’s respective standard deviations are 1.40, 1.59, and 1.24. The system’s power storage, peak-clipping, valley-filling, and other features have a greater impact than the flexible energy use of a standard structure. The building’s flexible energy use has a good peak shaving effect, which can compensate for the problems caused by the general battery energy storage system’s power and capacity limitations during the generation capacity period. In addition, the battery energy storage system can use the valley time to charge, resolving issues with valley filling optimization and the lack of flexible energy use in buildings. From this, it can be seen that the power storage system and the building’s flexible energy use jointly regulate the overall energy use performance of the structure, which not only achieves good peak load cutting and valley filling effect but also controls other issues such as frequent load fluctuations, large load peak valley difference, and other issues, ultimately leading to high energy utilization in China.

Fiber reinforced polymer (FRP) has been extensively used to strengthen concrete columns. It is necessary to establish peak stress model with high prediction accuracy for FRP-confined concrete columns. A theoretical peak stress model of actively-confined concrete is proposed based on Jefferson’s failure criterion. And a peak stress model for columns with circular sections (or concrete cylinders) is developed via the above theoretical model. By introducing the corner radius ratio ρ, a novel strength model for square concrete columns (or prisms) is further established. The proposed peak stress models are in good agreement with the experimental data covering the range of cylinder diameter D = 76 mm-610 mm, prism’s side length B = 100 mm-400 mm and the unconfined concrete strength f’c0 = 19.4 MPa-169.7 MPa. The established peak stress models are efficient due to the simpler expressions and high prediction accuracy.

Quenching is a conventional production process of wear-resistant steel, which has a decisive effect on the properties of wear-resistant steel. In this paper, the effects of quenching treatment on microstructures and mechanical properties of NM450 wear-resistant steel were investigated by optical microscopy and scanning electric microscopy. The results show that during the process of heating temperature of 880 °C and air cooling to 850 °C before quenching, the ductility and toughness of NM450 were improved significantly, whose comprehensive properties are better than 880 °C or 850 °C direct quenching steel. With the proportion of ferrite increasing, the strength of NM450 decreases, but the toughness doesn`t increase as influenced by grain size and grain boundary segregation. The martensite of intercritical quenching NM450 appears a shape massive, not lath.

In order to effectively detect the waveform characteristics of the closing inrush current of distribution transformers and distinguish between the magnetizing inrush current and the fault current when closing, this paper proposes a new method based on neighborhood preserving embedding (NPE) and principal component analysis (PCA) transformer closing inrush current detection method. This method can detect and process the global and local feature information of the data. First, the NPE-PCA algorithm is used to reduce the current data to two-dimensional space, and then the fitting error σ is obtained by fitting the two-dimensional space data. The relationship between σ and a given threshold is used to identify the magnetizing inrush current when closing. Finally, a model is built on the ATP/EMTP platform to test the proposed method for detecting the waveform characteristics of the closing inrush current. The simulation results show that the NPE-PCA inrush current waveform detection algorithm proposed in this paper can effectively identify the waveform characteristics of the transformer closing inrush current, which is consistent with the second harmonic wave. Algorithm comparison analysis shows that the performance of this algorithm is better.

The increasing data acquisition information in the distribution network brings new challenges to the monitoring and management of the distribution network. Therefore, this paper proposes a visual inspection system of a distribution network based on UAVs. The overall system hardware and UAV flight control power supply hardware are designed. The distance between the UAV and the obstacles is calculated by detecting the duration of laser signal reception. The visual inspection of the UAV obstacle avoidance power distribution network is carried out. The visible light, infrared, and laser data are fused, multi-source data are processed cooperatively, and the visual inspection information is collected and summarized. The test results show that the system has high efficiency and can provide accurate information for power system operators and managers in a relatively timely manner.

In order to improve the real-time performance of information transmission of power emergency communication system, the construction and inspection technology of power emergency communication system based on Beidou is proposed in this paper. Firstly, the differences between heterogeneous networks are described based on Beidou short message. Then, the fusion probability of heterogeneous network is calculated, and the optimal communication channel is obtained. Next, communication channel link is established, and the maximum transmission range is described. In addition, the network capacity is calculated, the congestion avoidance model is established, the bandwidth is obtained by defining the interference index of the information transmission channel, the total load during the construction and inspection process is calculated, and the construction and inspection of the power emergency communication system are realized.. Experimental results show that the proposed technology has better performance in information utilization, network throughput and system response time.

In recent years, transmission line icing disasters occur frequently, which poses a great threat to the operation of power grid. Most of the existing studies do not consider the impact of time-varying meteorological conditions on conductor icing. In order to effectively predict the growth of line icing, it provides an important reference for transmission line deicing and galloping early warning. The wind tunnel model of the transmission line is established by using the computational fluid dynamics simulation software, and the air flow field distribution around the transmission line is calculated by using the hybrid grid division. By establishing the motion equation of cooling water droplets in the air and analyzing the motion trajectory of water droplets, the local collision coefficient between water droplets and the transmission line is obtained, and the icing surface of the transmission line is discretized into a control body, Through the establishment of thermodynamic model, the mass balance and energy balance equations are established to calculate the icing quality of transmission line. According to the environmental temperature, wind speed, transmission line diameter and other factors, the quantitative influence degree of different factors on the icing form of transmission line is output, so as to provide technical support for the safe and stable operation of important transmission channels.

Most of the transmission poles and towers are built in the wild, and are often subjected to various loads such as wind, rain, ice and snow, especially the collapse of the tower caused by wind disasters. In order to study the response characteristics and disaster risk of towers under the wind field, this paper takes a 110kV transmission line as an example, and builds a “three towers and two lines” model based on ANSYS. Relevant specification parameters are calculated for the tower and conductor loads in this wind field, and the wind pressure time history is generated; based on the ANSYS transient analysis, the load wind pressure time history is used to analyze the dynamic response of the tower line, and the model is obtained in the static and dynamic wind field. Under the stress and displacement results, the response characteristics were analyzed. The research results can provide reference for tower design and line disaster prevention and mitigation.

Aiming at the problem that in the research and development process of the intelligent ship perception system, the fuzzy understanding of the perception demand causes the perception equipment to be inconsistent with the ship’s autonomous collision avoidance needs, based on the application practice of the 1972 “International Maritime Collision Avoidance Regulations” and the good marine craftsmanship of the mariners Based on the comparison and experience summary method, the ship pilot’s perception of navigation obstacles is analyzed, and the requirements for intelligent ship navigation perception at sea are proposed from five aspects: vision, ARPA radar, AIS, human-computer interaction, and electronic chart, it can provide theoretical support for the research of intelligent ship sensing system.

In orbit deployment and profile maintenance are the most important functional requirements in the development of loop antenna If the antenna cannot be deployed in orbit, it will lose the signal transmission function, and the profile in orbit holding function is related to whether the antenna can stably transmit electromagnetic signals. The mesh tension (main mesh tension, rear mesh tension and tension arrays tension) is the key means to maintain the profile stability in orbit. At the same time, it is also closely related to the rod load and the maximum motor driving force in the process of antenna deployment. Based on the theory of flexible multi-body dynamics, the dynamic modeling of the deployment process of ten meter loop deployable antenna is established in this paper On this basis, the influence of mesh tension on the deployment dynamics of loop antenna is analyzed by using the control variable method, and its related variation law is obtained. This study can provide guidance for the tension adjustment in the profile adjustment stage of the ring antenna, so as to shorten the development cycle, and can also predict the deployment of the antenna in orbit.

The main interference source of axle counter is the over-current caused by the operation of circuit breaker by intercity train. This paper focuses on the simulation modeling technology of switching over-current of intercity train circuit breaker. Firstly, the mechanism of the interference when the circuit breaker is closed is studied by theoretical analysis; Then, the interference source model is established when the circuit breaker is closed, and the equivalent circuit model of interference path including vehicle body, vehicle body grounding system, traction network and high-voltage cable is obtained through calculation and analysis. The current of transformer primary grounding wire is measured on the actual vehicle, and the accuracy of the model is verified by comparing with the simulation model. Finally, the spectrum characteristics of the interference current in the rail are obtained by Fourier transform. In this paper, a simulation modeling method for analyzing the operating overcurrent of intercity vehicle circuit breaker is proposed, which can effectively evaluate the magnitude of the interference current generated by closing the circuit breaker into the rail, and provide a research basis for the follow-up study of the interference characteristics of the radiation field of rail current on the trackside axle counter.

This paper presents an effective Self-Knowledge Distillation (SKD) framework via Atrous Spatial Pyramid Structure (ASPS), which is able to enhance the performance of the object segmentation network without increasing network parameters. In the framework, a lightweight object segmentation network is constructed to achieve the pixel-level object segmentation efficiently. A SKD learning model, including the SKD representation structure based on ASPS and loss function, is proposed to transfer the knowledge in the ASPS into our object segmentation network and improve its generalization ability. The experimental results confirm that compared with recent typical object segmentation networks, our object segmentation network contains the fewest parameters but achieves better performance. Moreover, the proposed SKD method achieves the best performance-boosting compared with recent SKD methods

Meteorological radar technology has a very important application in power grid disaster prevention and mitigation. Radar technology is used to measure related disaster information, so that people can better take preventive measures and reduce the impact and loss of disasters on the power grid. Using the detection data of meteorological radar, the types of severe weather are automatically identified and divided, and objective short-term nowcasting and forecasting are automatically carried out. The generated early warning products are organically combined with the geographic information system to realize the accurate forecast of short-term severe weather, and accurately locate the power grid equipment through the spatial analysis service engine.

UAVs with computer vision functions have been widely used in various fields. However, due to the limited memory and computing power of embedded devices, the real-time scene analysis of detection algorithm running on UAV platform is still a challenge. To face the challenge, in this paper, we based on the YOLOV3 detection model by changing the convolution method and using fewer parameters to generate more feature maps. We evaluate our detector on the VisDrone2020 dataset. Compared with the original YOLOV3, we achieved impressive results, including a reduction of 76.38% of the parameter size, 77.95% of floating-point operations, and a considerable accuracy rate and faster inference speed.

This article is a comparative study of tungsten (W) and molybdenum (Mo) samples manufactured by selective laser melting (SLM).Under the processing parameters different microstructural and mechanical properties like strain energy density, micro-hardness and surface morphology were investigated. Before the preparation of samples the SEM and XRD images were taken to calculate the size of micro particles of both the samples. These samples were further investigated by OM(optical microscopy),SEM(scanning electron microscope),EBSD(electron backscattering diffraction) and Vicker hardness to study the crystallographic structure, hardness, grain boundaries to understand a brief comparison between these two fourth group elements. It was identified as the cause of a very prominent structure with cracked features and a residual remains. During processing, different processing factors were examined, which separates at the edges of the grain, thereby creating thermal cracks. This due to the low eutectic melting compared to the matrix phase. These factors also result in a higher Ductile-to-Brittle Transition (DBTT). Later, during rapid cooling from the melting point, a combination of cracks with hot cracks on the borders of solid grain grains and cold cracks near weak grain edges forms a cracked network, which is often found in tungsten and molybdenum refined SLM. Neither does a very hot substrate plate prevent the formation of cracks in the metals formed by processing parameters. These materials are appropriate for high temperature up to more than 20000C such an analytic and inner wall constituents of fusion reactor or experiments. Parameters like laser power, scan speed, hatching space and the thickness of the powder layer are analyzed to achieve the high density samples. Three-dimensional printing is changing the way we make things in almost every industry, from cars to medical equipment to biotech.3D printing to prototype one of the most critical enabling technology in a building, the heat exchanger. In comparison to current designs, this next-generation heat exchanger weighs 20% less, performs 20% better, and can be produced much faster.

Dust–cloud–surface radiation interactions are a complex nonlinear relation referring to the influences of both atmospheric dust and dust-on-snow on surface albedo. A ‘Tiramisu’ snow event occurred on 1 December 2018, in Urumqi, China, providing an excellent testbed for exploring the comprehensive effect induced by atmospheric dust and those deposited atop fresh snowpack on surface radiation. A detailed analysis indicates that the decrease of snow albedo by 0.17–0.26 (22%–34%) is contributed by the effects both the dust–cloud interactions and dust-on-snow at synoptic scale in this case. In particular, dust well mixed with ice clouds at altitudes of 2.5–5.5 km disrupted the ‘seeder–feeder’ structure of clouds and heterogeneous ice nucleation. Dust-induced changes in the low layer of ice clouds (3.3–5.5 km) under a low temperature of –20 °C resulted in a 31.8% increase in the ice particle radius and 84.6% increase in the ice water path, which acted to indirectly buffer the incident solar radiation reaching the surface. Dust particles deposited on the snow surface further caused snow darkening since the snow albedo was found to decrease by 11.8%–23.3%. These findings underscore the importance of considering the comprehensive effect of dust–cloud–radiation interactions in the future.

With a large number of wind and solar power sources connected to the power grid, higher requirements are put forward for the power generation equipment to respond to the power grid imbalance. The safety research of generator rotor retaining ring under the impact of negative sequence current is of great significance. For 300MW turbogenerator, the two-dimensional and three-dimensional eddy current, temperature rise, stress and life of generator rotor under the impact of negative sequence current are analyzed and studied. The two-dimensional calculation models of stator and rotor are established, and the distribution of negative sequence eddy current field in rotor section is analyzed; considering the contact resistance between rotor and retaining ring and the end effect of magnetic field, a three-dimensional analysis model is established, and the calculation results of three-dimensional eddy current field, temperature field and stress field are obtained. The analysis shows that after considering the contact resistance between rotor and retaining ring and end effect, the current density at the contact between retaining ring and rotor big tooth edge is 17.6 times of the two-dimensional calculation result of rotor section, and the maximum temperature of rotor retaining ring reaches 170.36°C.

A broadband coherent perfect absorption (CPA) scheme consisting of an optical resonator coupled with three-level atoms excited by single cavity mode is proposed and analyzed. We show the output light field from the system is completely suppressed under specific conditions when the system is excited in linear and nonlinear regimes by two identical light fields from two ends of optical cavity. An analytical broadband CPA criterion for central and sideband excitations of cavity quantum electrodynamics system is derived in linear regime. Moreover, we show the resonant excitation criterion for CPA is greatly extended in nonlinear regime. A new type of bistability behavior is found. The output field intensity and the bistability curve can be well tuned by dynamically adjusting system parameters. Our results demonstrate that the CPA is quite universal, and it should be useful in a variety of applications in optical logic and optical communication devices.

Surface temperature responses to radiative perturbations due to aerosols and clouds are complicated by the land surface properties. To disentangle these complexities, this study, from a terrestrial surface energy budget perspective, isolates the underlying biophysical processes from the instantaneous radiative effects of aerosols and clouds on surface temperature using the National Center for Atmospheric Research Community Earth System Model version 1.2.1. It is found that in comparison with the global heterogeneous distributions of instantaneous radiative perturbations at the surface induced by aerosols and clouds, the spatial variations of the corresponding surface temperature responses to aerosol direct radiative effects (DRE) during the daytime and cloud radiative effects (CRE) during the nighttime are amplified. It is because of the consistent global distribution of the local surface climate sensitivity (a function of land cover properties such as surface roughness and Bowen ratio) with those of daytime DRE and nighttime CRE. By applying identical anthropogenic aerosol and precursor emissions over eight major past, present and projected future anthropogenic aerosol emitting regions (i.e. Brazil, China, East Africa, India, Indonesia, South Africa, United States and Western Europe), surface temperature responses to aerosol radiative cooling in the daytime and cloud radiative warming in the nighttime over these regions positively regulated by local surface climate sensitivities are prominent.

The 25mm DH36 steel was welded by hybrid laser arc welding (HLAW), and a sequence coupled thermal-metallurgical-mechanical (TMM) model was developed based on SYSWELD. The temperature-microstructure-stress fields are predicted by simulation verified by experiment. The ratio between the arc and laser energy showed a significant effect on weld profile. The laser provided the main power and ensured deep penetration, and the arc power showed a dominant effect on the bead width of the hybrid weld during HLAW. For the hybrid welding of a thick-walled plate, the microstructure and thermal cycles varied along with the thickness. The weld profile and microstructure were experimentally characterized. The 3-pass welding procedure produced larger welding residual stress than the 9-pass welding procedure, and the process stability is poorer than the 3-pass welding process. Overall, numerical results matched well with experimental results.

The embedded discrete fracture model (EDFM) method is used to study the mechanism model of the reservoir with a complex fracture system, and the sensitivity analysis of the development effect is carried out. The results show that: 1) the EDFM method can directly characterize the fracture morphology and fracture attributes in the reservoir; 2) Through comparative analysis of reservoir type, capillary force, and fracture development degree, it is found that different reservoir types have great differences in development effect, fracture opening has little influence on the reservoir, capillary force and fracture density have a great influence on the reservoir development effect, and with the increase of fracture density, the reservoir development effect increases significantly.

Under the goal of carbon peak and carbon neutral, it is of far-reaching significance to focus on the coordinated trading mode design of the Vehicle-to-Grid subjects in the electricity market and carbon market. However, there are few researches on the Vehicle-to-Grid subjects participating in the trading mode of electric carbon market by predecessors. Therefore, this paper, by combing the basic connotation of the Vehicle-to-Grid subjects, designs the trading mode of the Vehicle-to-Grid subjects in the electricity market and the carbon market, and further discusses how to get through the coordinated trading mode of the Vehicle-to-Grid subjects in the electric carbon market. In this way, relevant suggestions are given to strengthen the technical support of the Internet of Vehicles platform and improve the market trading mechanism.

A heuristic algorithm was presented to compute certain subgraphs for symmetric traveling salesman problem using frequency quadrilaterals. If we choose a set of frequency quadrilaterals containing an edge to compute the frequency for it, the frequency of an edge contained within the optimal Hamiltonian cycle approaches an extreme value as the city number is big enough. A heuristic algorithm was designed to compute a frequency graph with randomly selected frequency quadrilaterals. A subgraph containing the optimal solution was computed according to a given frequency threshold. The experimental results illustrated that in certain instances for Euclidean TSP with scale above 1000, the number of edges in complete graph is reduced by more than 30 times. Moreover, the bigger the number of frequency quadrilaterals is used, the higher the frequency threshold is and the smaller the number of edges in the subgraphs is kept.

Mobile Edge Computing (MEC) is considered as a key technology to support 5G networks. It can push cloud computing functions to the edge of the network, and achieve the purpose of reducing latency and reducing energy consumption through computing offloading and edge caching. In the MEC system, by caching computing services from the cloud center to the network edge, MEC can provide users with more services, and also be able to make greater use of network resources and improve system performance. However, which services to cache at edge nodes and how to cache these services have become an important challenge of the research. In order to solve the aforementioned problems, in this paper, we analyze the popularity of each cached object firstly, and propose a novel service caching algorithm, which aims to reduce system delay and improve resource utilization. In addition, we design a novel cache replacement algorithm that successfully predict future requests by analyzing historical data, thereby greatly improves the cache hit rate. Finally, experiments prove that our algorithms have greatly improved system performance and hit rate.

The Data-driven methods have been widely used in the SOC, SOH and energy estimation of electric vehicles, and they are recognized as the most promising approaches. However, the popular machine learning methods used for electric vehicles are often “black boxes” which result in the poor interpretation of the model. In this paper, a highly efficient gradient boosting decision tree (LGBM) is proposed to accurately estimate the driving range of electric vehicle. In this model, the feature importance scores are provided to discover the relationship. In addition, the proposed LGBM-T model is capable of generalizing the abstractions by taking into account the key features of time and temperature. Experimental results illustrate that the proposed LGBM-T algorithm is able to reproduce the driving mileage trajectory, with a low mean absolute error (MAE) bounded by 1.681% on real-world vehicles under complex operating conditions. The availability of this algorithm is further corroborated by comparing to the support vector machines (SVM) based estimator.