The Proceedings of the 18th Annual Conference of China Electrotechnical Society

The research on the insulation performance deterioration mechanism of switchgear insulators and the mechanical performance degradation mechanism of circuit breakers under actual working conditions is of great significance for the real-time evaluation of switchgear working status and the management, operation and maintenance of power transmission and distribution system. In this paper, the electric-wet-thermal accelerated aging test platform is established, and the accelerated aging test is carried out for the insulating parts of the switchgear which has been in service for 20 years. The insulation deterioration law and insulation failure mechanism of switchgear insulating parts under the combined action of electrical, wet and thermal factors are obtained. This paper can provide a theoretical basis for the condition evaluation of switchgear and the operation and maintenance of equipment under actual working conditions.

The safe operation of electrical equipment is very important to the stability of power system. In recent years, bionic sensing technology is a hot research topic at home and abroad. Bionic olfactory sensing technology has been successfully applied to food inspection, quarantine, search and rescue and other fields. The technology can also be used to detect defects or faults of electrical equipment, electrical equipment by detecting metal conductors and gas, liquid or solid insulation medium specific odor molecules emitted, and then identify defects or faults of equipment, and can be combined with visual and auditory diagnostic analysis. This paper first summarizes the development process of bionic olfactory sensing technology, expounds the principle, technical characteristics and research progress of three generations of bionic olfactory sensing technology, and discusses its application scenarios and development direction. Secondly, from the perspective of fault identification of gas, liquid and solid insulation media, the application of bionic olfactory sensing technology in the field of power equipment condition detection is studied, and their advantages and disadvantages are analyzed. Finally, combined with the re-search and application status of electrical equipment condition detection technology, the development direction and research prospect of bionic olfactory sensing technology in power equipment condition detection are pro-posed.

Axial magnet bearing has the advantages of adjustable stiffness and strong adaptability. However, when it is integrated into the magnetic levitation system of high-speed, the length of axial and radial often limit further applications. In traditional design methods, empirical formulas are often used, which will fail to obtain optimal values. Aiming at this problem, an optimization design method of axial magnetic bearing is proposed. According to finite element analysis, distribution of suspension force and magnetic induction intensity can be obtained. Moreover, local sensitivity analysis is carried out by quadratic response surface method to determine variables with high correlation about the objective function. Taking maximum suspension force, axial length and radial length as optimization objectives, thickness of thrust plate, length-width ratio of wire slot, air gap and slot fill factor as design variables, multi-objective optimization design can be carried out by multi-objective genetic algorithm, which will obtain optimal solution of structure parameters. Results show that maximum suspension force of the optimized one increases by 8.79%, the overall axial length decreases by 9.18%, and the overall radial length decreases by 6.92%.

This article mainly focuses on the design of rooftop distributed photovoltaic systems and the selection of access modes. Promoting rooftop distributed photovoltaic power generation throughout the county is one of the many ways to utilize solar energy. However, due to the diversity of urban buildings and the uncertainty of photovoltaic power generation, the effectiveness of this method has been difficult to achieve expectations. This article combines the operational characteristics of photovoltaic panels, the exploitable area of rooftop photovoltaic, and other factors to design rooftop photovoltaic systems for typical buildings at different levels, and analyzes the rationality of the access mode. The research results of this article can effectively further improve the operational efficiency of rooftop photovoltaic systems, and have practical guiding significance for accelerating the promotion of rooftop photovoltaic systems.

The increasing occurrence of extreme natural disasters has presented significant challenges to the distribution network. It is essential to assess the resilience of the distribution network in coping with such disasters. However, there is currently no unified standard for evaluating resilience. This paper proposes a resilient evaluation method for the distribution network based on mechanical mapping. Firstly, the paper divides the impact of extreme disasters on the distribution network into three stages: pre-disaster, in-disaster, and post-disaster, using the performance curve of the distribution network. Secondly, the paper constructs a resilient representation model of the distribution network for the in-disaster and post-disaster stages. The resistance stage in the disaster is mapped to the compression process of a spring in mechanics, and the recovery stage is mapped to the extension process of the spring in mechanics. The paper derives the expressions of the resilience coefficient of resistance and the resilience coefficient of recovery, as well as the relationship between the resilience coefficient and other resilience indices. Finally, the feasibility and effectiveness of the proposed method are verified using the modified IEEE 33-node distribution network.

With the increase of new energy penetration in the grid and the involvement of active management in the distribution network, new challenges are brought to the planning of optical storage. Therefore, this paper addresses these problems and introduces a three-tier planning framework with multiple objectives for optical storage in networks taking into account the management of energy consumption on the consumer side and grid refactoring by considering the economics and stability of distribution network operation, and proposes a hybrid solution strategy combining multiple algorithms and a “modified ring network coding method” based on the complexity of the model. By improving the variational operator and redistribution operator in the frame reconstruction algorithm, the infeasible solutions such as “island” and “ring network” are avoided in the frame reconstruction process. Finally, the efficiency of the suggested model and combined approach is verified by simulating the IEEE-33 node ADN, and the impact of demand-side management and network reconfiguration on the planning results is investigated.

The fault characteristics of photovoltaic (PV) systems are greatly influenced by environmental factors, which causes grand challenges in PV fault detection. Therefore, this paper proposes an anomaly detection algorithm for grid-connected PV system via anomaly-transformer. Firstly, a PV platform was built to carry out fault experiments under different meteorological conditions, and a total of 218 sets of DC voltage/current datasets were constructed. Aiming at the characteristics of multi-dimensional time series data, the multi-branch anomaly-attention mechanism is used to calculate prior-association and series-association, then use transformer to reconstruct the loss values based on the obtained data. The association discrepancy is calculated as the index of anomaly detection, so as to achieve the goal of time-based localization of PV faults. The experimental results show that compared with graph deviation network (GDN), unsupervised anomaly detection (USAD) and other algorithms, the Precision of anomaly-transformer reaches 76.45% and 95.41% respectively in sunny and cloudy test data sets, and the F1-score reaches 86.65% and 97.65% respectively. It can accurately locate the fault time, which provides an effective method for PV fault detection.

Since all major high-voltage cable projects currently use cable metal sheath grounding as an important safety protection measure, it is inevitable that sheath circulation will be generated in the cable, resulting in increased temperature rise of the cable metal sheath, reduced load capacity, accelerated insulation aging and other adverse effects. Therefore, based on the ATP-EMTP software, this paper establishes the sheath circulation model of the cable and analyzes the sheath circulation characteristics of the cable by selecting physical quantities such as cable ampacity and phase spacing, and proposes a method to suppress the cable sheath circulation. Meanwhile, a model of cable insulation ground fault is built in ATP-EMTP, and a preliminary method to determine the type and distance of insulation fault is proposed using sheath circulating current.

The consequent-pole permanent magnet synchronous motor (CPPM) has flexible pole arc coefficients. However, the pole arc coefficient significantly influence the cogging torque. In this article, the relationship between the pole arc coefficient and cogging torque of CPPM was derived by establishing a Fourier series analytical expression for the unit airgap magnetic permeability and the rotor permanent magnet magnetic excitation using the energy method. Firstly, the equivalent magnetic circuit model of CPPM was established using magnetic circuit analysis and Fourier series methods, and the influence of the pole arc coefficient on the cogging torque was analyzed. By using an unequal pole arc coefficient combination and skew slots, the cogging torque could be weakened. Secondly, through finite element simulation analysis, the cogging torque of different pole arc coefficients and unequal pole arc coefficient combinations were compared to verify the effectiveness of the proposed methods for reducing the influence of the pole arc coefficient on the cogging torque.

In order to improve the stability and economy of the power system after the grid connection of distributed energy, the “load similarity” feature is introduced to improve the clustering algorithm. The power and heat loads are divided into different time levels according to the daily load demand and other indicators, and the power of the distributed unit is matched according to the power and heat load supply and demand relationship corresponding to different levels of load. The idea of “Destroy And Repair in Particle Swarm Optimization” (DAR-PSO) was introduced to optimize the scheduling optimization model of micro grid. Based on the DAR-PSO load matching strategy, compared with the conventional strategy, the power load supply and demand deviation rates decreased by 2.03%, 2.37% and 2.88% in different load stages, and the heat load supply and demand deviation rates decreased by 1.15%, 2.51% and 1.64%, respectively. The total operation benefits of micro grid were increased by 1.40%, 6.15% and 3.86% respectively, which improved the economic benefits of micro grid operation.

In this paper, a method to perform the fault diagnosis of the drive system of vehicle-mounted hybrid excitation synchronous motors, combining particle swarm optimization and chimpanzee optimization algorithm (PSO-ChOA) with variational mode decomposition (VMD), approximate entropy for fault feature extraction and extreme learning machine (ELM) is proposed. First, a model of a six-phase hybrid excitation synchronous motor is constructed and six typical faults are simulated. Second, the classical variational mode decomposition algorithm is used to extract the feature vectors of the 7 states (including normal state) of the model from the fault signals. Finally, in order to effectively extract the features of the six-phase motor signals and perform diagnosis, the proposed chimpanzee optimization algorithm is used to optimize the key parameters of variational mode decomposition and extreme learning machine, respectively, which improves the accuracy of six-phase motor fault diagnosis. The experimental analysis results show that the fault identification accuracy of the method reaches 99.27%, which can identify motor faults more effectively than traditional algorithms.

The fault occurrence in a distribution network results in unstable operation and even damage throughout the power system. The effective fault location method is benefit for identifying the fault section which reduces and suppresses the adverse impact of faults on the system. This paper proposes a novel fault location method based on dynamic quantum genetic algorithm to locate the fault line. The method combines the dynamic rotating gate strategy and adaptive quantum crossover strategy to improve the requirements of quickness and accuracy for fault location. And a quantum mutation mechanism based on discrete coefficient is used to avoid falling into local optimum easily. We built a fault location model based on the evaluation function with anti-false positive factor. The dynamic quantum genetic algorithm is employed to generate random status for the lines. A generic switching function is proposed to convert it to the uploaded switch status of FTU. Combining the evaluation function, the fault location result is obtained by using dynamic quantum genetic algorithm. A distribution network is considered to validate the feasibility of the proposed method. The simulation results show the method can locate fault section accurately under the single or multiple faults and FTU signal distortion.

There are many advantages of the fiber-optic communication, and who occupies an important position in the power communication network of the state grid. The important business carried by the fiber-optic communication in the system of the state grid is expounded in this paper, and as an example of a provincial power company, the distribution of the reasons for the break out of the communication optical fiber cable in the recent four years is sumed up. The causes of the external breakage in power optical cable are analyzed, and the measures for preventing the external breakage of power optical cable are probed in this paper. Through typical cases, which provides an important reference for the communication and maintenance personnel of power system.

In order to predict the fuel consumption of ships more accurately, a GA-LSTM-ARMA prediction model based on wavelet transform is proposed. Firstly, the time series of fuel consumption is decomposed using wavelet transform, and the linear series is predicted by ARMA model, the nonlinear series is predicted by LSTM network rolling, then the above two series are stacked as the total time series prediction value. Finally, the GA algorithm is used to optimize the problem that the LSTM is prone to fall into the local optimal solution. The model was tested using the voyage data of the vessel "OCEAN FAVOUR", GA-LSTM-ARMA prediction model shows a significant accuracy improvement over LSTM, achieving a 12.5% error reduction.

In order to obtain power quality disturbance information accurately and efficiently, a power quality disturbance detection method based on lifting wavelet and fast Fourier transform (FFT) is proposed. Firstly, we use Euclidean algorithm to realize db4 wavelet transform, and verify the characteristics and shortcomings of lifting algorithm in processing transient and steady-state disturbance signals. Then, fast Fourier transform is carried out on the reconstructed steady-state component by utilizing the decomposition and reconstruction characteristics of lifting wavelet transform, so as to make up for the defects of steady-state disturbance processing by lifting wavelet and realize accurate and fast detection of transient and steady-state complex disturbance. The mode maximum is used to judge power quality disturbance in advance. The simulation results show that the proposed method can judge and deal with power quality in complex cases involving transient state and steady state, and has higher positioning accuracy and accuracy than traditional wavelet transform, which verifies the accuracy and efficiency of the proposed method for power quality disturbance detection

Introduced the current development of distributed energy and the impact of large-scale wind power integration on relay protection. The grid connected models of two types of wind turbines were built based on MATLAB/SIMULINK, and the short-circuit current characteristics of different types of wind turbines in case of short circuit at the outlet were analyzed through simulation, as well as the short-circuit current characteristics of the same type of unit with different grid connected capacities. A circuit model for connecting wind farms to distribution lines was built and theoretical calculations were conducted. The fault current characteristics of wind power connected and not connected were compared through simulation. The results showed that under the joint action of transition power group and wind farm impedance, wind power connected will cause a decrease in upstream fault current, affecting the selectivity and sensitivity of relay protection.

The processing defects of printed circuit board (PCB) are important factors causing the failure of electrical equipment. The processing defect detection of PCB must be followed up in real time. This paper Aims at the problems of too many manual designs, complex calculation process and unbalanced positive and negative samples in the PCB defect detection method based on two-stage Anchor, a PCB defect detection method based on Single-Stage Anchor-free is proposed. This method improves the FCOS algorithm, extracts features through the fully convolutional network, predicts the location of PCB defects through different levels of the feature pyramid networks, improves the accuracy of defect detection through three branch tasks of classification, regression and centrality, and adds an attention module based on swing transformer to the head. The whole process is Single-Stage, and PCB defect detection in the way of pixel level prediction. This method does not rely on the Anchor mechanism at all, and avoids the complex operation of Anchor. The experimental results show that this method can accurately detect all kinds of PCB defects, such as mouse bite, open circuit, short circuit, spur etc. The average detection accuracy of this method reaches 96.2%, and the detection speed is greatly improved compared with the method based on Two-Stage Anchor improves the detection speed. This method has certain theoretical value for the research of Anchor-free PCB defect detection method.

This paper focuses on the research of multi-port energy router for low voltage DC microgrid. Firstly, a multi-port energy router based on DC bus architecture is proposed. Then, design the control strategy of each port of the energy router. The AC side port adopts the J and D adaptive improved virtual synchronous generator control with the introduction of pre-synchronization control. Considering that the inconsistent state of charge (SOC) will lead to the overcharge and overdischarge of part of energy storage. An improved droop control based on the state of charge of energy storage is designed in the DC side port. Finally, considering the SOC, peak cutting and valley filling, load mutation, emergency access and other factors, the DC bus voltage hierarchical coordination control strategy of energy router is designed. And the Matlab/Simulink simulation platform for a variety of switching simulation experiments. The results show that the energy router can recover stability quickly in the face of various emergencies.

The gas information in oil-immersed transformers is an important parameter in the identification of the insulation condition Three-element mixed insulation oil is a new type of insulating liquid, which has been safely used in transformer insulation systems. There is an urgent need to develop fault diagnosis method for three-element mixed insulation oil transformers. In this paper, the transfer characteristics of different types of gases between oil and paper insulation in the three-element mixed insulation oil-cellulose system are studied through simulation. The results show that when the initial position of gas is in the cellulose, the greater the absorption force between cellulose and gas, the more difficult for the gas to transfer from the cellulose to oil. When the initial position of gas is in the three-element mixed insulation oil, the larger the free volume fraction of gas molecules in oil and cellulose, the easier gas transfers from three-element mixed insulation oil to cellulose. The conclusions contribute to improving the accuracy of the fault diagnosis for three-element mixed insulation oil transformers based on dissolved gas analysis.

The As a key technology for the realization of self-driving cars, the merit of trajectory tracking control directly determines the stability, safety and comfort of vehicle driving. In order to explore the performance of existing mainstream trajectory tracking controllers under different vehicle speeds, this paper designs three types of methods, PI- pure tracking, PI-Stanley and PI-MPC, and obtains the trajectory tracking effect by changing the key parameters of controllers, so as to grasp the parameter design laws of different methods. Firstly, a vehicle system dynamics model is established based on the assumption of planar motion, to guide the design of the trajectory tracking controller. Secondly, the trajectory tracking controller is divided into longitudinal controller and transverse controller, the longitudinal controller is designed based on PI control theory and the transverse controller is designed based on pure tracking theory, Stanley control theory and model predictive control theory respectively. Finally, a double-shift test condition is built based on Carsim/Simulink to verify the performance of the designed method at different vehicle speeds.

A power IoT abnormal flow warning mechanism based on wavelet decomposition and LSTM is proposed to address the issue of abnormal flow warning on the IoT management platform. Through wavelet decomposition, random and non-stationary time series can be stabilized to reduce data volatility. Through LSTM model, relevant temporal information of time series can be learned. Firstly, wavelet decomposition is performed on the time series to divide it into multiple dimensional time series. Then, LSTM models are used to predict the decomposed time series, and the predicted time series is obtained through wavelet reconstruction. By predicting the time series and inputting the time series, a sliding time window is selected to dynamically determine the warning threshold. When system flow is detected to exceed the warning threshold, relevant warnings are given. The experimental results indicate that this mechanism can effectively predict future time series and provide early warning for abnormal flow in the system.

This paper introduces an accident of the first protection differential protection action and the second protection starting unaction of a main transformer caused by an external fault of a 110 kV substation, the cause of the first set of protection differential protection action of the main transformer is the three-phase short-circuit grounding fault of the 10 kV line on the low-voltage side of the substation, at the same time, the main transformer’s first set of protection for the 10 kV side B phase differential current circuit is damaged at the secondary terminal connection of the current transformer, the current sampling of the first differential current circuit of the main transformer in 10 kV line fault is incorrect, which is not consistent with the current increase of 110 kV side and 35 kV side, cause the first set of protection ratio differential protection b-phase action jump off the main transformer three-side switch. According to the actual situation of the site and the analysis of the cause of action, the relevant solutions are put forward, which provide a reference for the prevention and solution of similar accidents.

Based on Maxwell transient electromagnetic field model and Fluent transient flow field model, the multi-physical field numerical simulation model of electromagnetic coil with water-cooled structure was established, the temperature field and flow field are calculated. In this model, the simulation results of the transient current with armature are taken as input, and the coil current distribution of the water-cooled pipeline under the action of the transient current is calculated. The cooling effect of water-cooling mode under continuous launch was analyzed and compared by coupling the wall of coil and water-cooling body directly. The results show that the temperature of the coil can be significantly controlled by water cooling, but the pressure drop of the water channel increases nonlinearly with the increase of the velocity, and the pressure drop exceed 1 MPa at 2 m/s, therefore, water pressure and structure should be taken into account in the selection of water cooling flow rate.

To achieve the rapidity, accuracy and stability of speed tracking of autonomous electric vehicle under different working conditions, four methods, namely Fuzzy PID, Feedforward PID, Sliding Mode Control and conventional PID, are designed in this paper for comparative analysis. Firstly, a parametric self-tuning Fuzzy PID controller is designed using a combination of fuzzy control and PID control. Secondly, a Feedforward PID controller was designed based on the inverse longitudinal dynamic model of the vehicle and PID control. Thirdly, the sliding mode surface function was designed according to the longitudinal dynamics model of the vehicle and the principle of sliding mode variable structure, and the appropriate sliding film convergence rate was selected to obtain the sliding mode controller. Finally, control simulation software and vehicle dynamics software were used for joint simulation tests and comparisons. The results show that under some common operating conditions, the combined control effect of Fuzzy PID and Feedforward PID is slightly better than that of conventional PID, and the Sliding Mode Control is significantly faster than the other three PID controls in terms of response speed, but it is slightly worse in terms of control accuracy. In some complex working conditions, the comprehensive control effect of Fuzzy PID is significantly better than other control algorithms, which can effectively improve the accuracy and stability of control.

Aiming at the interference problem of multiple signals generated by the coupled source of orbital electromagnetic kinetic energy accelerator on the acquisition of measuring instruments, a generative Heterogeneous of wavelet Transform (GHT) method is proposed, which combines the characteristics of different physical quantities to map the collected data waveforms into the generated heterogeneous space, and accurately identifies and measures complex signal waveforms. Firstly, a set of multi-physics coupling field shock signal waveforms were collected by electromagnetic kinetic energy acceleration test, and the waveform decomposition accuracy indicators (DAM) of STFT, CWT and GHT were compared to define the signal decomposition accuracy metrics (DAM), which verified the decomposition characteristics of GHT on complex shock waveforms. Secondly, the one-dimensional time-domain waveform is converted into a two-dimensional time-frequency domain image, and an Image classification of seed growth clusters (ISGC) is established, and the results show that GHT can decompose and filter the signal image with impact noise signal, current signal and speed signal interference to obtain a clearer pulse waveform, which proves the correctness and feasibility of the proposed method.

Stable operation of transformers is critical to ensure power supply safety in the grid. At lower temperature conditions, the physical state of moisture inside oil-paper insulation changes significantly, significantly changing the dielectric properties. The traditional oil-paper insulation state assessment method does not consider the impact of changes in the physical state of moisture, which lead to inaccurate assessment results. In this paper, laboratory tests were conducted on oil-immersed pressboard samples with varying moisture content to analyze the frequency dielectric response across a temperature range of −40 to 100 ℃. The influence of changes in the physical state of moisture on the relaxation activation energy of oil-paper insulation was analyzed. The double translation calculation method for the relaxation activation energy of damp oil-immersed pressboard over a wide temperature range was proposed. It provides an essential theoretical basis for assessing the insulation state of the transformer at low temperatures.

In recent years, the engineering practice shows that the VSC has obvious drawbacks when it is connected to weak grid. It is easy to cause insufficient voltage support at PCC point of power systems. In order to solve this problem, this paper proposed an instantaneous voltage control method by using the integral characteristic of filter capacitance, which is also based on the instantaneous current control method. Because there is only one low leakage reactance transformer between the external potential of VSC and the PCC point, the two are strongly connected, which can effectively control the voltage of PCC point. At first, this paper analyzed the principle of PCC instantaneous voltage control method. Then, the frequency response and stability of the proposed method are analyzed in the complex frequency domain. In the electromagnetic transient simulation software, the voltage support capacity and fault ride through ability of the proposed method is simulated and verified. Finally, this paper compared the proposed method proposed with the other existing method - the proposed method is simpler, more reliable, and more widely applicable and has strong voltage support capacity and fault ride through ability, which can provide key technical support for the construction of new power system dominated by new energy in the future.

In order to solve the problem that the voltage exceeds the limit and the reactive power flow fluctuates violently after the high proportion of new energy is connected, which leads to the problem that the action of reactive power compensation equipment in the substations is too frequent. This paper proposes a reactive power and voltage control method for regional grid considering the optimal regulation cost. First, dynamic partitioning is carried out according to the topology of the power grid, and then establish an optimization model with the optimal regulation cost as the target to solve the voltage and branch reactive power control objectives of each node, and finally an advanced decision-making control strategy is carried out. At the same time, in order to solve the problem of insufficient model convergence caused by the high fluctuation rate of new energy power flow, a correction algorithm based on “pre-action” is introduced as a supplement to meet the high real-time online control requirements. It is proved that the method has a good effect on reducing the action numbers of reactive power compensation equipments in substations, and effectively improves the optimal scheduling level of reactive power in regional grids.

In this paper, to solve the gradual difficulty of traditional power frequency withstand voltage and partial discharge tests in meeting the insulation detection requirements of on-site primary equipment, as well as the problems of large weight and volume, transportation and operation difficulties of traditional impulse withstand voltage test devices, this article introduces the basic principle, circuit structure, and common impulse voltage waveforms used in impulse withstand voltage tests of impulse voltage generators, and takes the design of 2400 kV/240 kJ impulse voltage generators as an example, The core parameters and overall design of the system have been completed. On this basis, a prototype of SF6 insulated integrated impulse voltage generator system was developed. At the same time, the relevant test results show that the performance indicators of the designed impulse voltage generator meet the test requirements, and can effectively solve practical problems such as the difficulty of on-site impulse testing for ultra-high voltage GIS and other substation equipment, with strong application value.

Vision Transformer (ViT) shows a great potential in the field of bearing fault diagnosis by virtue of its multi-head self-attention mechanism. However, ViT confines the one-layered convolutional network to the feature map preparation and its accuracy is hindered by the insufficient local features caused by noise interference in practical scenarios. To address this problem, a local feature expansion based ViT, i.e., LFE-ViT, is proposed. A hybrid convolutional residual network is introduced to the embedding module to expand the local information of the bearing faults. Then, by combination of the local feature expansion network and the following multi-head self-attention mechanism, the completely local and global feature representation is achieved for the bearing fault classification. Finally, the derived ViT model is validated on the Case Western Reserve University bearing dataset. The experimental results have shown that it gives better diagnostic performance compared with existing methods under the noise environment.

The electronic transformer is affected by factors such as running time and environment, and the error performance in the long-term operation process is not stable enough to cause inaccurate energy measurement. This paper proposes an online error compensation method for electronic transformers based on Stacking integration algorithm. Firstly, the mutual information (MI) coefficient is used to reduce the dimension of the original feature set to obtain the optimal correlation feature set. Then, the high correlation features are used as the input of the model, and the K-fold (KF) cross-validation method is used to train each sub-model. Finally, the real-time error of the transformer is predicted and the error of the transformer is calibrated online. The example analysis shows that the prediction loss of the proposed method is less than 5 %, which is applied to the output compensation of the secondary end of the 0.2 stage transformer, so that the measurement accuracy of the transformer is improved to 0.1.

The mechanical characteristics of the asynchronous induction electromagnetic coil driving device were calculated using the finite element method. A numerical model of the driving device was established in two-dimensional axisymmetric cylindrical coordinates, and a four node rectangular ring element was used for calculation by assuming the symmetric distribution of physical quantities in the circumferential direction. Using stress and strain as the solution variable, establish a mechanical equilibrium equation in the driving structure region to solve the displacement field of the structure. Based on the boundary conditions of force and displacement, obtain the spatiotemporal changes of stress and strain. The model considers inter turn insulation, excitation timing, and the mechanical properties of the GFRP material used, and can be used to calculate the time-varying magnetic field, electromagnetic load, and structural response of the driving device in the domain. Based on the numerical calculation results, a driving structure for modular assembly with bidirectional separation of shaft diameter is proposed.

Power theft has a large impact on both power supply enterprises and power users, and in view of the huge amount of data required for some existing power theft detection methods based on machine learning data analysis and the problem of low accuracy, this paper proposes a power theft identification method that integrates clustering and improved sparrow search algorithm. First, the FCM clustering algorithm is used to classify the typical daily load curves of the users and form a “portrait” of the user’s electricity consumption behavior; second, by calculating the matching degree of the load curves to be tested and the user’s electricity consumption behavior “portrait”, the “suspected” electricity theft detection method is locked in place and the “suspect” electricity theft detection method is applied. Secondly, by calculating the matching degree between the load profile to be tested and the “portrait” of the customer’s electricity consumption behavior, the “suspected” customer is locked; finally, the “suspected” customer is further detected by using the Improved Sparrow Search Algorithm (ISSA). Experimentally, the proposed method combined with FCM clustering algorithm can narrow the detection range of power theft users to a greater extent, and the improved sparrow search algorithm can accurately locate power theft users, which greatly improves the efficiency and accuracy of power theft detection.

To promote low-carbon economic operation of integrated energy system (IES). This article proposes an operational optimization scheduling model that considers carbon capture (CC) equipment and demand response (DR) under a carbon tax mechanism. Firstly, the basic model of IES was established. On this basis, considering the response of CC equipment and electric heating demand, an IES carbon tax mechanism model was established. Finally, taking the minimum sum of energy purchase cost, operation and maintenance cost, response compensation cost and carbon tax cost as the objective function, combined with IES multi-energy flow operation constraint, a low carbon and economic operation optimization scheduling model was constructed, and CPLEX was used to solve it. By setting up five scenarios for example analysis, the simulation results show that the introduction of carbon tax mechanism considering the IES of CC equipment and DR reduces carbon tax by 67.33% and total operating costs by 18.24%. The simulation results further show that the introduction of CC equipment and DR Under the carbon tax mechanism can flexibly transfer the load, reduce the operating cost of the system, and reduce the carbon emission of IES, which has potential application value.

With the construction of offshore wind power projects, cross-linked polyethylene (XLPE) submarine cables are gradually applied to low frequency power transmission. However, the electrical aging characteristics and mechanisms of XLPE at low frequency remain unclear. In order to study the effect of low frequency electrical aging on the electrical conductivity current characteristics of XLPE and its difference from power frequency electrical aging, accelerated electrical aging experiment of XLPE films are conducted under applied AC voltage of 20 Hz and 50 Hz. The electrical conductivity current characteristics of XLPE films are measured at different electric field strengths after 3, 6 and 9 days of electrical aging. The results show that the conductive currents of XLPE increased with the growth of accelerated electrical aging time at both low frequency and power frequency. The conductivity current increases from 6 pA to 147 pA after 9 d of aging at power frequency, and from 6 pA to 307 pA at low frequency. The conductive current increases more at low frequency than at power frequency, the 20 Hz conductivity current is 80%, 63% and 52% higher than the 50 Hz conductivity current at 3 d, 6 d and 9 d aging, respectively. In addition, the electric field remains above the charge injection threshold for a longer period of time in a single cycle at low frequency, so the low frequency voltage enhances the charge carrier mobility and space charge trapping probability in the insulating medium, generating more thermionic and causing more polymer chain breaks, resulting in higher conductivity currents under low frequency aging compared with power frequency.

With the increasing penetration rate of inverter distributed power sources year by year, traditional short-circuit current calculation methods are no longer applicable. Therefore, this article proposes a short circuit current calculation method for IIDG distribution network based on an improved BP neural network: using the optimal voltage support strategy, the IIDG fault is equivalent to a current source model controlled by the voltage of the grid point. The feature decomposition method is used to improve the sample feature and label selection process of the BP neural network, extract key features and sample labels, and combine common features to obtain the features and sample combinations of the BP neural network. System modeling and network training were conducted in an IEEE33 node system, and compared with traditional short-circuit current calculation methods to verify that the proposed method can effectively solve the short-circuit current calculation problem of distribution networks containing IIDG and has high accuracy.

According to the special live detection work of infrared accurate temperature measurement carried out in a 110 kV substation during peak winter load, this paper found that the temperature of B-phase arrester at the middle voltage side of the 110 kV main transformer is abnormal, and the leakage current of this phase arrester is larger than that of the other two phases. Carried out insulation resistance, DC reference voltage and leakage current testing after power outage. After disassembling, it was found that there were abnormal phenomena such as surface oxidation of aluminum support parts and obvious traces of water inlet inside the B-phase arrester. After disassembling, insulation resistance test was carried out on each valve plate. It was plate overed during the pressurization and infrared temperature measurement testing that the valve plates were abnormal. It was determined that the reason for the abnormal temperature of the arrester for phase B is its long-term dampness. At least 6 of the 13 valve plates have deteriorated, indicating that the arrester for phase B has entered the accelerated deterioration phase. B phase arrester has entered the deterioration accelerated stage. In addition, suggestions and conclusions are put forward for the abnormal heating of arrester, and preventive measures are proposed to avoid the defects affecting the safe and stable operation of power grid equipment.

The unbalanced magnetic pull force is mainly caused by the asymmetry of the magnetic field. The analytical solution calculation of unbalanced magnetic pull force under saturation and load conditions is very complex, and numerical solution methods are generally used for calculation. This article takes a certain type of hydroelectric unit as an example and uses different calculation formulas based on the no-load characteristics to calculate the unbalanced magnetic pull force, providing a theoretical basis for dealing with the poor stability of the unit caused by unbalanced magnetic pull force in engineering sites. From the analysis, it can be seen that the empirical formula method, numerical analysis method, and discrete solution method are used to calculate the unbalanced magnetic pull force of the generator, and the calculation results of centrifugal force formed by the rotor counterweight on site are compared. The discrete solution method has the highest accuracy and the most accurate calculation results, which can provide a good basis for practical engineering applications.

High-voltage circuit breakers (HVCB) are the key equipment for power transmission in high-voltage grids. For the problem that the traditional classification algorithm does not have high accuracy for fault diagnosis of HVCB in the case of insufficient fault data. This paper proposes a method based on reconstructing the feature matrix and sliding windows to improve the random forest algorithm. First, the Gini index is used to feedback the relative importance of all features and determine the distribution of important features, which is then used as a basis to reconstruct the feature matrix. The reconstructed single sample is then divided into multiple subsamples using the sliding window method, and all of them are used in the training of the decision tree after indicating their labels. The proposed method not only improves the diagnostic accuracy of the traditional model, but also performs better in small samples.

The online monitoring data of transformer oil temperature plays an important role in judging the reliability of transformer operation and monitoring the internal insulation state of transformer. However, due to the complex environment where the oil temperature sensor is located, failures are very easy to occur, so the monitoring data may appear abnormally due to sensor failure. The resulting abnormal data affects the judgment of the state of the transformer. Therefore, this paper first analyzes the abnormal types of sensor data, and then proposes an abnormal detection approach for transformer oil temperature sensor data based on Informer. The proposed approach can identify various abnormalities in long-term oil temperature monitoring data, and experiments based on multiple transformer oil temperature monitoring data verified the effectiveness and high accuracy of the proposed method.

Optimization the structural parameters can ameliorate the electric field distribution characteristic of electric fittings. Therefore, selecting the model parameter by orthogonal experiments, we established the plane test model using the finite element analysis software ANSYS to study the electric field distribution influenced by radius of the pendulum, length of swing arm and the swing angle. According to the range analysis results, it can be seen that the radius of pendulum is the most influential factor, followed by the length of the swing arm and the swing angle. The variance analysis results show that the most significant influences are radius of pendulum and length of swing arm, the swing angle is no sense. Though the calculations, corona test is carried out in this paper. The tendency of corona inception and extinction voltage with arm length and pendulum radius diameter were obtained. The research results can provide the reference date for practical engineering and a reference for the design and selection for application of UHV transmission line.

In 750 kV transmission line, all kinds of circuit breaker closing operations, such as three-phase null line of circuit breaker and single-phase reclosing when single-phase ground fault occurs, will produce a high overvoltage on the transmission line. The value of this overvoltage often exceeds the required value of system insulation coordination, causing certain damage to the transmission line. In order to solve the above problems, this paper takes Shanghai Miao Converter Station - Shahu 750 kV transmission line as an example, based on the ATP-EMTP electromagnetic transient simulation software to establish a 750 kV circuit breaker three-phase closing and single-phase reclosing operation overvoltage calculation model. The influence of closing resistance of metal oxide arrester and circuit breaker on 2% statistic overvoltage of three-phase closing and single-phase reclosing is calculated and analyzed. Finally, the arrester configuration limiting the operating overvoltage and the closing resistance value of the circuit breaker are determined.

The high penetration of distributed generations is playing a significant role in distribution systems owing to its environmental and economic advantages and power supply flexibility. Distributed generation-based flexibility and reliability of intentional islanding in distribution networks become an important means to maintain power supply to critical loads under fault conditions, which can effectively improve the power supply reliability of distribution networks. However, the self-organizing recovery process of intentional islanding generates large voltage amplitude and frequency fluctuations, which affects the safe and stable operation of islanding and leads to network failure in serious cases. Therefore, this paper proposed a network fluctuation smoothing strategy based on a multi-agent consistency algorithm, designed a distributed frequency-voltage hierarchical control framework, considered the coupling of local information and communication time delay, and adopted a proportional integral control protocol to solve the communication time delay problem. The Lyapunov function is introduced to prove the stability of the proposed strategy and to quantitatively determine the upper bound of the delay. Simulation results show that compared with the use of traditional droop control, the improved control based on the multi-agent consistency algorithm has a stronger anti-interference capability, which can significantly attenuate the voltage and frequency fluctuations in the process of islanding self-organizing and the instantaneous integration of islanding into the main network, and can improve the system dynamics and the power quality.

Aiming at the large torque ripple problem of the permanent magnet assisted switched reluctance motor, an adaptive control for the turn-on angle and turn-off angle is proposed in this paper. Firstly, for the problem that the parameters of BP neural network are difficult to determine, the NSGA-II multi-objective genetic algorithm is used to optimize its parameters so that the network prediction output is more accurate. Then, select the appropriate angle datas for various working conditions and use it as the training output data of the BP neural network prediction model. Finally, the simulation results show that: under different speed and load conditions, the control strategy proposed in this paper realizes the angle adaptive adjustment, reduces the current amplitude and torque ripple.

By adjusting the voltage on one side of the loop closing point to the maximum extent close to the voltage on the other side, the phase-shifting transformer can achieve close loop closing with the same source, reduce the loop closing current and cross the power flow, providing an economic and effective technical scheme for the loop closing to power supply. The polarity of the voltage regulating winding and phase regulating winding and the gear selection of the on load tap changer are the key to the accurate voltage regulation of the phase-shifting transformer, and are the decisive factors to realize the closing loop to power supply. In order to overcome the disadvantage of the poor adaptability of the table lookup method to determine the gear and polarity of the phase shifting transformer, this paper proposes a control method for the gear and polarity of the dual core asymmetric phase shifting transformer based on the voltage vector four quadrant analysis method. Firstly, the model and regulation principle of dual core asymmetrical phase shifting transformer are introduced; Then, a new scheme of power supply based on phase-shifting transformer is proposed; Then, a dual core asymmetrical phase-shifting transformer based on voltage vector four quadrant analysis method is proposed; Finally, the proposed control method is simulated and analyzed in PSCAD simulation software, which verifies the effectiveness of the method and the feasibility of applying it to the closed loop power supply control.

A method based on kernel density estimation theory is suggested to examine the influence of time-of-use power prices on electric car charging demand on distribution network voltage quality. Firstly, a random charging load model for electric vehicles based on the Monte Carlo approach is created, and the electric vehicles charging load model under different user response coefficients η in time-of-use electricity price is also established. Secondly, probability flow calculation formed by Monte Carlo method simulation is used to form kernel samples, and then a kernel density function is constructed. After that, an importance sampling simulation is carried out, and the probability flow solution is used to analyze the node voltage. Four indicators, node voltage limit violation probability, node voltage fluctuation index, node voltage confidence level, and confidence interval, are used to evaluate the distribution network's quality of voltage. The effectiveness and viability of the proposed method are demonstrated by the simulation results.

With the release and implementation of the “double carbon” policy, a large number of new energy sources with fluctuating and intermittent characteristics are integrated into the power grid, and the stability of the power system is challenged. Therefore, how to ensure the safe and stable operation of the power system is now a key issue to be solved. The traditional means of frequency regulation relies on thermal power units, but it has low efficiency of frequency regulation, which is harder to adapt to the new track of the current rapid development of the power grid. Compared with thermal power units alone, battery energy storage systems assist thermal power units to participate in frequency regulation can solve most of the problems of thermal power units alone. In this paper, we construct a power system model from the principle of grid frequency regulation, and verify the reasonableness and necessity of battery storage system participation in frequency regulation with thermal units alone and battery storage system-assisted thermal units respectively. The frequency regulation effect of the traditional thermal unit frequency regulation and the joint thermal storage model are compared, and the variable coefficient sag control is simulated in the joint thermal storage model, and the fuzzy PID algorithm and the artificial neural network (ANN) algorithm are added to the joint thermal storage model, which has obvious superiority compared with the traditional thermal unit frequency regulation. Among them, the fuzzy PID algorithm is the most effective, which can produce a small change in the frequency scale value, followed by the ANN algorithm and the combined fire storage frequency model.

Aiming at the dual PWM frequency converter with rectifier and inverter side independently controlled, expensive bulky capacitance must be added to the DC side to keep the voltage stable, which will increasing the cost and reducing the life of the entire system, a dual PWM variable frequency speed regulation system which the rectifier side adopts dual-close-loop control using current inner loop and voltage outer loop, and the inverter side adopts the rotor magnetic field orientation vector control with SVPWM technology was proposed in this paper, and use load current feed forward control strategy to achieve the coordinated control of dual PWM converter by means of making load current feed forward to net side. The obtained simulation results indicate that compared with the independently controlled dual PWM variable frequency speed regulation system, the integrated coordinated control strategy of dual PWM variable frequency speed regulation system can not only reduce the harmonic of the network side current, but also inhibit the fluctuation of DC voltage during the load mutation, accelerate the dynamic response of the rectifying side and the inverter side, greatly improve the resisting disturbance ability of the system, thus reduce the capacity volume and reduce the cost.

This paper introduces the equivalent circuit of the current transformer (CT) represented by “Γ” type. Then, the relationship between the inductance, resistance, and excitation current in the excitation branch of the CT's equivalent circuit is explained according to the definition of excitation current provided in the standard GB 28040.2 (IEC 61869-2). Furthermore, the factors that influence the CT's excitation current and error, which include the magnetic permeability, losses, structural dimensions of the magnetic core, and resistance of the secondary circuit, are analyzed. This analysis serves as a theoretical basis for predicting changes in errors resulting from adjustments in material characteristics during the CT's long-term operation. Additionally, it can be utilized as a theoretical basis for the CT's design and performance improvement.

The accurate calculation of the transient temperature rise during cable operation is of key importance for the dynamic capacity enlargement system, and it’s a challenge to calculate the impact of thermal coupling effects between cables when solving the transient temperature rise for the multi-circuit cable. In this paper, a decoupling method is applied and a transient thermal circuit model based on thermal coupling coefficient method (TCCM) is proposed to quickly calculate the transient temperature rise of a double-circuit trench cable. The transient thermal circuit model of a double-circuit trench cable is established, and the parameter values of heat source, thermal resistance and heat capacity of the thermal circuit model are determined by IEC standard and finite element method (FEM). For the double-circuit trench cable, a heat source is introduced to consider the thermal coupling effects from the adjacent circuit, and TCCM is used to determine the value of the added heat source. The results show that the transient circuit model of double-circuit trench cable based on TCCM can accurately calculate the transient temperature rise of the cable under eight different step loads, and the maximum deviation between the results of TCCM and FEM is within 1 K.

Due to the strong electric field near the Ultra High Voltage (UHV) transmission lines, there are increasing complaints about induced electrical problems in greenhouses near the lines. In this study, a model of a 1000 kV double-circuit AC transmission line and a steel-framed greenhouse was established to investigate the effects of different shielded wire parameters on induction electricity in the greenhouse. The simulation results were analyzed based on the maximum information coefficient. The study found that the correlation between different shielded wire parameters and induction electricity in the greenhouse was ranked from high to low as follows: installation height, the horizontal distance from the greenhouse, the number of shielding wires, and spacing between shielding wires. The installation height had a significant impact on the induction electricity value, while the correlation between the spacing between shielding wires and induction electricity was relatively low.

The turbine with power load unbalance protection (PLU) can restrain the rotor speed rise and avoid speeding when a turbo-generator unit meets load rejection. However, due to the poor reliability of power measurement, it is easy for the PLU protection to malfunction and bring serious impact to the safety and stability of the unit when operators take improper operation or measurement problems take place. A dynamic simulation model is established, which can simulate the dynamic performance of the overs-peed protection control (OPC) and the PLU protection, the influence of the action on the unit speed, power, main steam pressure and other parameters when the load rejection occurs. In addition, the life of the unit can also be evaluated by this model. Then an example of a 1050 MW ultra supercritical steam turbine is calculated and analyzed, in which the performance of over-speed protection system, changes of thermal parameters including rotor speed, unit power, main steam pressure, and so on in two cases of power load unbalance protection and no power load unbalance protection when the load rejection takes place. This paper gives discussion and analysis about the rationality of PLU protection in a turbo-generator unit.

Under the goal of carbon peaking and carbon neutrality, distributed resources are connected to the distribution network on a large scale, and the source, network, load and management of the distribution system have changed significantly, facing a series of new problems, which are highlighted in the digital control system, among which the existing distribution automation technology can no longer meet the growing demand for digital control of the distribution network. In this paper, we propose a control architecture for low- and medium-voltage distribution networks for different application scenarios such as centralized regulation and control of distributed resources and microgrid group cooperation, and verify it by application examples.

The A new type of faulty line selection in small current grounding system based on model recognition is proposed. When single phase grounding occurs in the distribution network, in different frequency range the zero sequence network equations of internal fault and external fault are constructed, then the model error is established. Model error of external fault is far greater than model error of internal fault for faulty line, however, model error of external fault is far less than model error of internal fault for sound line. According to this feature, fault line selection criterion is pro-posed, and no model parameter is required to be calculated. The simulation shows that the principle is not affected by the initial phase angle and transition resistance, and has high reliability.

In this paper, aiming at the defect of the original entropy weight calculation formula, this paper proposes a multi-objective decision making method which improves the entropy weight calculation method. Based on the single weighting method of the original entropy weight calculation formula, this method adds a complementary weighting method, and uses the mean value of the entropy value of each evaluation index to control the proportion of the two weighting methods, and combines the subjective weight of experts to get the comprehensive weight. Different entropy value types are tested to verify that the proposed method is more reasonable, in addition, this paper also takes Pareto solution set as an example to verify that the proposed multi-objective decision making method based on the improved entropy weight calculation method is feasible, simple and efficient, and more suitable for online operation.

The goal of “optimizing coal mine energy consumption” is clearly proposed in the intelligent coal mine construction guide (2021 version). In the “Evaluation and Management Measures for Intelligent Construction of Coal Mines” (2023 version) issued by Shanxi Province, it is explicitly mentioned that “green energy such as photovoltaic, wind, and gas should be used to achieve energy self-circulation”. In order to achieve the above goals and meet the growing high power demand in the coal mines, the paper adopted the high-voltage DC power supply line constructed by the dual electrical energy router cluster, and constituted with the existing AC supply line in the coal mine, formed a low-carbon, autonomous, and efficient coal mine hybrid distribution network. The topology and connection relationship of the electrical energy router and power quality management device were exampled. Also, the management platform function of the mixed distribution network was explained. The results indicated that the construction of the mixed low-carbon distribution network for coal mines can effectively reduce the cost in production activities, improve the proportion and efficiency of renewable energy, and reduce energy consumption costs in the coal mine production process without reducing the reliability of the power supply system.

The micro-grid multi-agent optimization operation including smart power users, EV charging systems and solar energy storage systems is currently an effective way to reduce fossil energy dependence. For the traditional multi-agent reinforcement learning algorithm, there is only one total objective function, which cannot determine the realization of each agent’s own goal. In this paper, a heterogeneous multi-agent reinforcement learning method is proposed to solve the problem of optimal operation involving different stakeholders. While achieving the maximum of the total objective function, it clearly shows the realization degree of each agent’s own goal. The heterogeneous multi-agent reinforcement learning algorithm is applied to solve the micro-grid optimization operation model of different investment entities including EV charging system, PV/wind/storage system and smart power users. The study shows that the heterogeneous multi-agent reinforcement learning algorithm can provide effective strategies for the multi-agent optimization of micro-grid, and effectively display the realization effect of the objective function of each micro-grid agent.

After years of grid use, composite insulators in electric power systems are subject to varying degrees of aging, including pulverization, elasticity, and hydrophobic degradation. The current nuclear magnetic resonance relaxation spectroscopy detection methods struggle to accurately reflect the specificity among insulators with various service lives. In this study, the aging state of several composite insulators was determined using an NMR relaxation spectrum analyzer with the same sequence control key parameters. The distinctive quantities of the aging degree detection were found, and the appropriate magnet temperature for measurement was investigated. The results demonstrate that the height and area of the wave spectrum can effectively reflect the aging degree of insulators, and the sensitivity and variability of detection results among different insulators can be best reflected at a magnetic temperature of 32 ℃.

The position-speed observation loop constructed by the conventional pulsating high-frequency injection method is contradictory in terms of both high-order harmonic suppression and observation performance. Meanwhile, the phase delay caused by the low-pass filter (LPF) in the position observation loop also seriously affects the load carrying capacity of the motor. In order to widen the observation bandwidth of the position-speed observation loop and weaken the negative influence of the LPF on the position-speed observation loop, this paper proposes an improved positionless control strategy based on the dual multi-parameter notch filter (DMPNF). Compared with the traditional notch filter, the DMPNF used in this method weakens the degree of coupling between different performance metrics, which can simplify the design process and at the same time improve the performance of the designed notch filter. This method has a wider stabilized observation range and is able to use a higher loop gain than the conventional method, while maintaining a strong suppression effect on the higher harmonics. Meanwhile, the dynamic performance of the position-speed observation loop is further improved by estimating the position compensation. In this paper, the conventional pulsating high-frequency injection method is first modeled and analyzed. Then, the proposed improved sensorless control strategy and observation position error compensation method are analyzed and presented. Finally, the effectiveness of the proposed method is verified by simulation.

The corrosion of power grid equipment will be accelerated by the high salt and humidity environment along the coast of Fujian, and its service life will be affected, and lead to the failure of equipment and structures. This paper mainly studies the change of the metal indicator composition of silver-Graphene composite coating hanging pieces with different Graphene concentrations in the coastal high salt and high humidity environment. The mechanism of silver-Graphene composite coating on the contact resistance of metal equipment in the coastal high salt and high humidity environment is analyzed by scanning electron microscope, XPS analysis and XDR analysis. The results show that the silver coating of traditional electrical equipment will produce dark products under the action of coastal high salt and high humidity environment β-Ag2S, thus improving the contact resistance, affecting the conductivity and the reliability and stability of electrical contact. The silver-Graphene composite coating can effectively reduce the generation of Ag2S, maintain good conductivity, and achieve corrosion resistance. However, the higher the concentration of Graphene, the better the effect.

With the development of economy and technology, HEMS (Home Energy Management System) will gradually become an important part of residents’ load. Therefore, it is of great significance to study the operation optimization of HEMS. Aiming at the problem that the user comfort evaluation index of HEMS is not comprehensive, this paper proposes an operation optimization strategy of HEMS that considers the user’s multidimensional comfort. Firstly, according to the operation characteristics of the household load inside the HEMS, corresponding mathematical models are established. Secondly, HEMS operation optimization model is established with the multi-dimensional comfort minimum as the optimization goal, and the model is quickly solved by MO-Jaya algorithm and fuzzy membership function. Finally, the validity of the model is verified by an example analysis under the TOU (Time of Use) price and the peak price.

Silicon is considered an excellent negative electrode material for lithium-ion batteries due to its abundant storage on earth and high theoretical specific capacity. However, the volume effect and poor conductivity limit its large-scale promotion. In order to solve the above problems, Si-Sn composite with controllable tin contents have been prepared in large scale by a simple electroless deposition method, where temperature successfully controlled the contents of tin. The synthesized compounds were identified as silicon-tin compounds by X-ray diffraction. The particle morphology of the Si powders after ethanol washed, Sn prepared by electroless deposition without Si and Si-Sn composites were observed by SEM analysis. The cyclic voltammetry (CV) curve of Si-Sn composites electrode shows distinct peaks related to the specific lithiation or delithiation steps corresponding to Si and Sn, which indicates that the metal Sn is successfully deposited on the surface of Si powders by electroless deposition. After Sn electroless deposition, the electrochemical performance is significantly improved.

Industrial load accounts for the largest proportion of the total social load, and tapping the potential of industrial load regulation is one of the best ways to achieve load regulation. This paper proposes a regulation strategy of industrial load demand response. Firstly, based on the electricity consumption characteristics of industrial loads, a mathematical model for industrial load regulation was designed. Different time scale issues were considered in the established model, providing different time scale scenarios for system regulation, with the goal of minimizing the total energy cost. Secondly, an improved bald eagle algorithm was proposed, which has stronger optimization ability compared to traditional bald eagle algorithms. Finally, through the IEEE-30 bus system, the optimal strategy of industrial load demand response is obtained. The simulation results of the example verify the applicability and effectiveness of the model and regulation strategy proposed in this paper.

The wide application of aramid fiber (AF) reinforced polymer composites in the electronic and power industries is believed to be restricted by the defects on the AF/resin interface. In this work, AF surface modification methods by atmospheric plasma and toluene-2,4-diisocyanate (TDI) treatment were used to improve the AF/epoxy interfacial performance. Composite winding tubes were prepared by modified AF and epoxy resin. Tensile strength of AF monofilaments was measured and the AF/epoxy composites were characterized by scanning electron microscope (SEM), dye penetration test and water diffusion test. Experimental results showed that unmodified AF/epoxy composites contained multiple interfacial defects, modified AF/epoxy composites had less area of penetration at the top surface in dye penetration test and showed better insulating performance in water diffusion test. The tensile strength of AF was not affected, the performance of the AF/epoxy interface was improved and the defects in composites were reduced after modification. The modification methods proposed in this paper has a good industrial application prospect.

The current transformer in the distribution network is the hub equipment for the transmission of current signals between the primary and secondary circuits. In order to effectively carry out anti-theft analysis and ensure the correctness of line topology information, it is necessary to detect and verify the operating transformation ratio of the current transformer. This article proposes a study on the online verification method for the transformation ratio of current transformers in distribution networks. Based on the advantages of big data and information technology in electricity collection systems, the law of energy conservation and the characteristics of distribution network systems are combined to achieve online detection and verification of the operating transformation ratio of current transformers, and to achieve accurate search and positioning of transformation ratio errors in current transformers. The online verification method for current transformer ratio proposed has obvious advantages such as high efficiency, good real-time performance, low safety risk, and no need for testing equipment, which is suitable for the development requirements of digital informatization.

The transformer hot spot temperature determines the operating state and useful life of the transformer, and accurately predicting the hot spot temperature can effectively improve the transformer maintenance efficiency. Therefore, a 10 kV oil-immersed stereo roll core amorphous metal transformer was used as the research object in this paper, and its multiphysics transient coupling analysis simulation model was established. Based on the results of multiphysics simulation, the Levenberg-Marquardt (LM) algorithm combined with the universal global optimization (UGO) was used to correct the correlation coefficient in the empirical formula of hot spot temperature calculation, thus to improve the accuracy of temperature prediction. The results show that the proposed method can improve the efficiency of the actual operation and maintenance of transformers.

In extremely cold regions, the dynamic viscosity concerning the transformer oil in the oil-immersed transformer will change in winter. The dielectric properties of the transformer's main insulation at low temperatures are significantly different from those at normal temperatures. As it is inevitable to carry out dielectric properties testing about transformers at low temperatures during the handover test of winter in some areas, it is very important to carry out research about the state assessment of oil-paper insulation at low temperatures. In existing standards, the reduction method for the oil-immersed power transformers’ dielectric dissipation factor does not consider the influence of insulation aging and the content of moisture. What's more, the reduction results at low temperatures have large deviations. In view of the above, this paper proposed the power frequency dielectric dissipation factor's equivalent reduction method concerning the transformer's main insulation at low temperatures, which is based on FDS test data concerning oil-paper insulation obtained under laboratory conditions in the wide temperature range. This method is combined with the equivalent model of dielectric relaxation for the transformer's main insulation and considers the content of moisture and the aging of insulation. It provides an important theoretical basis for the accurate evaluation of insulation state transformers.

In this paper, an integrated impulse test platform is designed to meet the requirements of the site impulse test. In order to solve the problems existing in the traditional GIS site impulse test, such as many kinds of equipment, large volume, difficult long-distance transportation, tedious installation and long preparation time, GIS site impulse test can be integrated, automatic and installation free. In order to test the feasibility of the platform design, three-dimensional model of the platform was established based on the three-dimensional modeling software PRO/E, and the force analysis and verification of the key components of the platform were carried out. The analysis results show that the designed integrated test platform can meet the performance requirements of the on-site impulse test in all aspects, and can greatly improve the test efficiency of the on-site impulse test.

Due to the influence of phase-to-phase coupling and space coupling, it is difficult to accurately extract the resistive current in the leakage current of the 1000 kV arrester, which affects the judgment of its health status. In this paper, the simulation calculation model of the real scene is established by scanning the 5 groups of 1000 kV surge arresters in the Jingmen UHV station, and the space capacitance matrix of the 1000 kV surge arresters is obtained, and the space interference current data is obtained based on the resistance-capacitance network theory and the simulation calculation of the road model. Comparing the simulation calculation results with the live detection results, the errors of the simulation data of each group of arresters are all within 5%, which verifies the correctness and feasibility of the simulation experiment approach, and conducts a resistive current test on the field measured data fix. The results show that the rapid construction of the complex three-dimensional solid model of the arrester and the surrounding electrified body can be realized through on-site Lidar scanning; the space interference current data of the arrester can be obtained through the simulation calculation of the field circuit model; based on the method proposed in this paper, the three-phase leakage of the arrester can be The full current is close to the state of no space coupling interference, and the resistive current extraction in the full current of the arrester is realized.

The forward kinematics and inverse kinematics of the leg of a quadruped robot are the basis of quadruped robot control. The relationship between foot position and joint angle through forward kinematics is the basis of foot velocity and joint velocity. The joint angles of the three joints of the leg can be directly calculated through the inverse kinematics, which can be directly used to drive the motor movement. In this paper, the forward kinematics model and formula derivation are established by analyzing the leg structure of a quadruped robot. The inverse kinematics uses geometric method to obtain the formula of each joint. The leg kinematics model is established by using the robot toolbox. The inverse kinematics calculation is carried out for two different positions and postures, and the correctness of the inverse kinematics calculation is verified in real robot.

The AC filter arresters in several converter stations of ultrahigh-voltage (UHV) and high-voltage direct-current (HVDC) transmission system have accelerated aging, and the measured impulse current waveform is different from the standard lightning impulse current waveform, which pulse width is longer. Therefore, in this paper, impulse aging tests with current amplitude of 27 kA were performed on zinc oxide (ZnO) varistors under negative polarity 15/35μs and 8/20μs impulse currents to explore the influence of different impulse current waveforms on the impulse aging characteristics of ZnO varistors of AC filter arrester. Firstly, according to the test to verify the repetitive charge transfer rating in IEC60099-4, two groups of new ZnO varistor samples were subjected to 10 groups of accelerated aging tests with two consecutive impulses with current amplitude of 27 kA. Secondly, the forward and reverse DC reference voltage (U0.1mA and U1mA), AC reference voltage (U*0.1mA and U*1mA) and residual voltage (U10kA) of the samples during impulse aging were measured. And then, we calculate the nonlinear coefficient and residual voltage ratio. Finally, the change trend and average change rate of electrical characteristic parameters of the two groups of samples during impulse aging were compared and analyzed. The results show that under the same amplitude of impulse current, the longer the pulse width, the greater the energy absorbed by the sample, the stronger the thermal aging effect, and the aging rate of the sample is relatively accelerated, but there is no direct relationship with the impulse current pulse width.

Based on the analysis that the fault outside the area caused by inconsistent current circuit wiring on both sides of A line leads to misoperation of differential protection of the line, the reason is that the protection device on one side of the line adopts phase A and C current as the local protection current, and the other side of the line adopts phase A, B and C current as the local protection current. The protection device on both sides of the line does not alarm or operate, which causes the differential protection on both sides of the line to operate incorrectly when the fault occurs outside the area. Through case analysis, the relevant countermeasures and handling methods are introduced to provide reference for the subsequent handling of similar incidents.

Heavy gas protection of the main transformer is used as the non-electric main protection of the main transformer. After a serious fault occurs inside the main transformer, the oil flow of the main transformer will impact the baffle plate of the gas relay, and the heavy gas device will act quickly and jump off the switches on each side of the transformer to protect the transformer [1]. This paper analyzes an event of the main transformer heavy gas protection maloperation caused by the fault crossing current outside the 35 kV transformer area, and analyzes the cause as the fault outside the main transformer heavy gas area, and the operation value of the main transformer heavy gas is less than the requirements of the regulations. The reliability of the heavy gas action is effectively improved by adjusting the action setting measures of the heavy gas relay in the main transformer according to the requirements of the regulations. To ensure proper operation of heavy gas protection.

The Space Environment Simulation and Research Infrastructure (SESRI) has a large number of devices and complex correlations. At the same time, the data files are diverse and not intuitive. In order to realize the life cycle management and service support of the devices in SESRI, this paper takes the Numerical Simulation and Central Monitoring System (NSCMS) in SESRI as an example to construct a knowledge map of equipment management. First, the equipment management requirements of SESRI were analyzed, and the hierarchical structure of the digital imitation central control system was determined; second, the equipment management ontology of the digital imitation central control system was designed based on the requirements using protégé; after that, the corresponding knowledge extraction scheme was proposed for various data sources, and the required triples were obtained to complete the data driving of the schema layer of the ontology and construct the knowledge graph; finally, the storage, updating and visualization of the constructed knowledge graph were realized using the graph database Neo4j.

Monitoring the abnormal states of power equipment in the Space Environment Simulation and Research Infrastructure (SESRI) is crucial to ensure the efficient and safe operation of these devices. This paper introduces a power equipment abnormal state monitoring strategy based on log analysis technology. The log parser, Drain, is used to analyze the log data of power equipment, transforming it into structured data. Subsequently, the Template2Vec algorithm is employed to convert this data into word vectors and segment it into log sequences. Next, an attention-based Bi-LSTM (Bi-directional Long Short-Term Memory) model is constructed to extract feature vectors from the log sequences, and these vectors are input into an SVM classifier to detect whether the log sequences are abnormal. Finally, the feasibility of the proposed strategy is validated using the HDFS log dataset from Loghub. Experimental results demonstrate that this strategy efficiently detects and identifies abnormal behavior in power equipment, thereby reducing equipment failures and downtime.

The tower foundation of transmission lines in mountainous areas often bears a large uplift force. As a new foundation form composed of central stub pile and multiple anchors around pile, the inclined anchor stub pile foundation can make full use of the bearing capacity of the surrounding rocks and has a strong uplift bearing capacity. In order to study the mechanical properties of inclined anchor short pile foundation joints. ABAQUS finite element software was used as the analysis tool. Based on the material constitutive model, frictional contact behavior, simulation method and theory required for modeling, numerical simulation of the uplift bearing capacity of inclined anchor short pile foundation was carried out, and the reliability of the finite element calculation was verified by comparison and analysis with the laboratory test results. The law of stress deformation and failure of foundation joints is studied. The results show that the experimental results are in good agreement with the numerical results, and the three-dimensional numerical model can be used for mechanical analysis of short pile foundation with inclined anchor. The failure of short pile foundation with inclined anchor starts from the node area under the action of uplift force, and the failure process can be roughly divided into four stages.

In recent years, with the rapid growth of new energy power generation in China, the construction cycle of wind and photovoltaic power projects is usually short. As a bridge between the new energy station and the power grid, the construction mode of the booster station will affect the construction period and quality of the power station. This paper firstly analyzes the comprehensive comparison of prefabricated cabin booster station and conventional booster station construction modes in eight dimensions, including Site selection conditions, covering area, station construction period, construction cost, site civil construction workload, site installation workload, equipment debugging, later expansion, and points out that the prefabricated cabin construction mode is more suitable for new energy substation construction with “standardized design, factory processing and prefabricated construction”. Then, focusing on the construction period optimization of the prefabricated cabin, studies the main reasons that affect the schedule of the prefabricated cabin from the design to the production and then to the construction, and puts forward the optimization suggestions of the whole link of design-production-construction. It provides reference for optimization technology of construction organization of large-scale prefabricated cabin.

Due to its high-power density and compact size, high-power permanent magnet synchronous generator for offshore wind power generation has become a global research hotspot for wind turbines. However, there are many technical problems in the electromagnetic and loss characteristics of MW-level high-power wind generators, which have become the difficulties that researchers need to overcome at present. The accurate calculation of electromagnetic performances directly affects the losses characteristics calculation, and the accurate calculation of losses is important to estimate the thermal characteristics and furthermore design. Due to the time harmonics and space harmonics, there is however an increase in the external losses, leading to challenges in accurately calculating losses. For the design and manufacture of high-power wind generators, accurate calculation of electromagnetic performances and losses characteristics is more important. In this paper, the accurate calculation of electromagnetic performances and losses characteristics for the high-power semi-direct drive permanent magnet wind generator for offshore is carried out. The corresponding theoretical analysis is verified by a prototype experiment. These studies will be valuable references in designing and developing high-power off-shore wind turbines.

Battery management systems (BMS) are primarily based on battery models for state estimation and management of lithium-ion batteries. However, variables that affect battery parameters include current, state of charge (SOC), temperature, etc. These variables also exhibit nonlinear coupling effects, making it difficult to establish an accurate battery model. Therefore, this paper proposes an electro-thermal coupled modeling method for lithium-ion battery. The method involves constructing models based on external characteristics data such as battery voltage and temperature. Firstly, multiple sets of constant current operating condition experiments are designed to obtain experimental data that include current, SOC, and temperature information. Secondly, the Arrhenius equation is selected as the architecture for the battery voltage model to describe the nonlinear relationship between voltage and temperature, with the quantitative influence of current and SOC reflected in the parameters of the equation. Then, the Bernardi model is chosen as the battery thermal model to estimate real-time battery temperature. Finally, the accuracy of this electro-thermal coupled modeling method is validated through experimental voltage data. The experimental results show that the modeling method is feasible and has high accuracy.

Energy consumption of central air conditioning is the main part of building energy consumption. Due to the immature control technology and business model of the central air conditioning system, unnecessary waste is caused in the operation process. Therefore, there is still much room to improve the energy consumption of the central air conditioning system. For this reason, the energy efficiency improvement method of large-scale air-conditioning system for multiple scenarios is studied in this paper, the simulation model of air-conditioning load characteristics in multiple scenarios is researched, and the adjustable capacity of air-conditioning load in different scenarios is summarized. In addition, the scheme of air conditioning load participating in power grid regulation is formulated. Combined with the characteristics of air conditioning load, the appropriate data is selected to predict the air conditioning system load, and the adjustable capacity of air conditioning load is obtained. Finally, according to the results of load forecasting and adjustable capacity of air conditioning load, the scheme of air conditioning load participating in power grid managing is formulated.

PSM (Pulse Step Modulation) technology is a combination of SM (Step Modulation) technology and PWM (Pulse Width Modulation) technology, and a wide range of output voltage modulation can be realized by this modulation. SPS (Switching Power Supply) module is the basic component of PSM high voltage power supply. It has a short response time while the voltage and power of this power system is very high. It is necessary to ensure that the power supply releases less energy when the power supply module is breaking down. In order to achieve a small amount of energy stored when the SPS module fails, the logic circuit is designed. The alternating current contactor is separated in time to cut off the input energy when the SPS module fails. In this paper, the logic circuit of SPS power module has been designed, which has the characteristics of simple structure, low cost, good reliability and strong protection ability. The simulations and experiments show that the alternating current contactor can be separated from the AC input power supply by the logic circuit in a short time, and the stored energy is very low.

In the substation, combined with the maintenance of protection, safety, measurement and control device, defect treatment or the adjustment of the power grid operation mode, sometimes it is necessary to throw back some protection, safety, measurement and control device pressure plates, and the voltage at both ends of the pressure plate must be measured before being put into the pressure plate. In addition, measuring the voltage potential at both ends of the pressure plate can correctly determine whether the function of the protection, self-safety and measurement and control device is normal and whether it can be put into. This paper analyzes the wrong switch tripping event caused by the wrong gear selection of multimeter when the operator is measuring the voltage at both ends of the platen. The development of a new intelligent voltage potential detection device at both ends of the platen can effectively solve the above problems.

In view of the problem of low-frequency oscillation caused by the coupling of traction power supply system and high-speed train, a small-signal impedance model of traction power supply system and high-speed train was established. The stability of the vehicle-network system was analyzed by the impedance ratio criterion, and the mechanism of low-frequency oscillation was revealed. On this basis, the influence of the control parameters of the train grid-side rectifier on the low-frequency stability of the vehicle-network system was analyzed, and some basic conclusions and rules that have a guiding effect in suppressing low-frequency oscillation were obtained. Finally, the theoretical analysis is verified in experimental test.

Magnetic coupling resonant wireless power transfer (WPT) technology has become a research hotspot in WPT technology due to its relatively excellent energy transmission performance. In this paper, an alternating magnetic field measurement system based on electromagnetic induction method was designed to study the spatial magnetic field characteristics of a magnetic coupling resonant WPT system. The weak induced electromotive force of the magnetic field is obtained through the thin cylindrical coil wound by the enameled wire. The digital signal of the output electromotive force of the magnetic sensor is obtained through the amplification circuit composed of the instrumentation amplifier and the analog-to-digital conversion circuit, and finally sent to the upper computer for data processing and analyzing through the single-chip microcomputer. A simulation WPT system and magnetic sensor models is established via software to achieve coupling results of the circuit and the magnetic field. Comparing the measurement and simulation results, the designed measurement system has more accurate results with small errors, and can be used for subsequent research on the spatial magnetic field characteristics of WPT systems.

Various characteristic states inside battery and data for function management system can be reflected by state of charge (SOC). Accurate SOC estimation plays a decisive role in safe and stable operation of battery management systems and electric vehicles, but the measurement error, battery nonlinearity, electrochemical reaction complexity, performance aging, temperature change and other factors affect the SOC estimation accuracy. For complex nonlinear system of battery, particle filter (PF) is used to predict SOC because of its advantages in nonlinear system, but particle filter algorithm also has problems of particle degradation and depletion. In this paper, the firefly algorithm (FA) is used to optimize the particle filter, and the position of the individual reflectivity and attraction is updated continuously to achieve particle optimization. To simulate the online state, a battery is selected to simulate the UDDS working condition, and the maximum estimated error of SOC is 0.43%.

The mechanical performance of the isolating switch in gas insulated switchgear (GIS) is crucial to the safety of the power grid, but existing methods cannot directly observe the contact stroke, and the accuracy needs improvement. Through theoretical and simulation analysis, this paper reveals a strong correlation between the residual voltage of very fast transient over-voltages (VFTO) and the contact opening distance. Then, the first-order difference of the residual voltage in the whole process waveform of VFTO is extracted as the discriminant feature. Furthermore, for the extremely unbalanced problem of the training samples in practice, the one-class support vector machine (OCSVM) is utilized to realize the online diagnosis task. Experiments show that this method can effectively identify typical mechanical faults such as sticking and rusting of the GIS isolating switch shaft.

The structural stress concentration caused by the large temperature difference in the field during the installation of generators will bring about problems of power quality and stability. In order to solve this problem, a short circuit drying test is carried out on the generator, and the vibration, spectrum characteristics, phase voltage harmonic distortion rate and telephone harmonic factor are calculated and analyzed before and after the test. Through the test and analysis, it is found that the stability parameters of the unit and the electromagnetic parameters of the generator are obviously improved, and the ideal power quality and safe and stable operation characteristics are achieved. The results show that this method can effectively release the stress concentration caused by the large temperature difference during the installation of the generator, make the magnetic circuit of the generator more uniform, improve the power quality, and provide a new scheme and basis for the solution of the power quality and stability of the generator.

The super-large truncated spherical radome, with a radius of over 25m, is almost at the limit of the rolling sphere method radius (30 m) prescribed for lightning protection requirements for Class I buildings. The traditional tower-type or rod-type radome lightning protection design often results in incomplete protection coverage and degrade radar performance due to reflected radar waves caused by its metal tower rod. To address these issues, this paper proposes a radome protection design scheme that employs multiple plasma wave-transparent lightning rods deployed along the diameter ray direction like a “hedgehog-type” deployment. Using COMSOL following the quasi-electrostatic field method, both plate and rod electrode lightning strike attachment simulations are carried out to evaluate the protection effectiveness of the proposed design scheme. The simulation results demonstrate that this hedgehog-type design scheme provides effective protection for the super-large radome.

The identification of the fault-types in power lines is the prerequisite for avoiding large-scale blackouts and restoring an abnormal or a faulty power system to its normal operation. Given an increasingly steady foundation for the application of artificial intelligence in power systems, machine learning has become one of the major directions applied to studying the fault problems in the systems. Performances of different machine learning algorithms may not be exactly the same in fault-type identification. In this paper the fault data of voltage and current obtained from a fault simulation model are collected and formed into sample sets. Five models of machine learning algorithms, i.e., one-dimensional convolutional neural network, principal component analysis & support vector machine, support vector machine, random forest, and K-nearest neighbor, are constructed and programmed in Python to identify various fault-types and then cross-validate their identification performances. After these models are trained in the training set, they are tested in the test set to obtain the values of such performance indexes as accuracy, precision, recall, and F1 score of the fault-type identification, and the confusion matrixes for the quantitative analysis of the misidentified and misclassified samples. The results show that the above five models built by the five machine learning algorithms perform significantly in identifying short-circuit fault-types, and all the values of the performance indexes exceed 98.81%. Especially, among them the model of the one-dimensional convolutional neural network outperforms the other four ones owing to its impressive overall performance.

Streamer branching phenomena are commonly observed in gas and liquid discharge processes, displaying significant randomness. The stochastic nature that drives streamer branching is primarily attributed to background noise during the initial state, impurities in the medium, and non-uniform distribution caused by fluctuations in carrier density. In this study, we propose a two-dimensional streamer model that incorporates carrier density fluctuations and investigate differences in streamer propagation under various externally applied voltage conditions. The results indicate significant variations in the propagation velocity of the main streamer channel under lightning impulse and pulse voltage conditions, while the size and quantity of streamer branching are influenced by both the excitation type and voltage magnitude. Higher voltages lead to faster propagation of the main streamer channel in the direction of the electric field and an increased number of streamer branches. The rising edge of the applied voltage determines the initiation time of streamer coronas and influences both the overall diameter and discharge velocity of the streamer channels.

Electrical power load plays an important role in keeping safety and security of power grid and systems. Tremendous attentions have been given in line with how to predict electrical load in an accurate way. However, there exists various uncertainties and influential factors leading to complexity of prediction or inferior accuracy. This paper has proposed an improved long short-term memory (LSTM) neural network with variable dimension reduction by employing gray correlation principle. The computational test results verify the effectiveness of the proposed scheme in short-term load prediction. The accuracy of the proposed method increases from 4.97% to 1.60% in MAPE while R2 promotes from 0.64 to 0.97 by comparing with BP neural network under the same case study. Moreover, the proposed algorithm has saved computational cost due to variable dimension reduction where the redundant dimensions are removed from the original historical data set by employing correlation analysis. The finding of the study will encourage real-time applications in future power grid since the proposed algorithm has relatively high prediction accuracy with less computational costs. The both benefits are essential to real-time applications in practical electrical power grid.