The increase in renewable energy penetration rate may induce the risk of power supply interruption and reduce the operation reliability of the power system. The traditional mid-long-term reliability evaluation method is challenging to meet the time requirement of operation reliability evaluation. This paper proposes an efficient evaluation algorithm for power system operation reliability, which reveals the analytical function relationship between the power system operation reliability index and uncertain factors such as wind power output. It avoids repeated reliability calculation when uncertain factors change. Firstly, the distribution characteristics of wind power output are modeled based on the hidden Markov model. Then, the analytical function between the reliability index and wind power output is established by the state enumeration-polynomial chaos expansion method. Finally, based on the analytical function, the efficient operational reliability evaluation and weak links identification of the new energy power system under real-time wind power output are realized. Taking the modified IEEE RTS79 system as an example, the effectiveness of the proposed method is verified.

The arcing fault inside a converter transformer will result in a sudden rise of oil pressure inside the tank, which may lead to tank rupture or even serious explosion and fire, seriously threatening the safe and stable operation of the power system. This paper takes the actual 500 kV UHV converter transformer as the research object, and carries out numerical simulations on the ANSYS platform to obtain the spatial and temporal distribution characteristics of the oil pressure inside the converter transformer during the arcing fault. The simulation results show that the gas bubble grows dynamically during the arcing fault inside the equipment, the oil pressure rises abruptly with the pulsation of the gas bubbles and shows obvious fluctuation characteristics, and the spatial distribution of oil pressure inside the converter transformer is uneven. This study has certain reference significance for the converter transformer pressure reduction and explosion-proof and structure optimization.

A novel single-stage three phase harmonic current injection Step-up/down (STHSUD) AC/DC converter is proposed in this paper. This proposal integrates a three-phase uncontrolled rectifier bridge combined with a post-stage Cuk module, and the low-frequency bidirectional switch is introduced to provide a path for the converter to feed back the harmonic current, so that the purpose of reducing the harmonic content of input current is achieved. Firstly, the topology and operating principle of the proposed converter are analyzed, its equivalent circuit is established, the voltage transfer ratio of the converter is deduced, and combined with hysteresis tracking control, the closed-loop simulation of the proposed converter is performed to prove the buck-boost capability. The control strategy is simple, and input current can be sinusoidal with high power factor. Finally, the experiments are carried out in the TMS320F28335 DSP digital control platform, and the experimental results verify the feasibility of the proposed topology.

Traditional active clamp flyback converters rely on the resonance between the transformer leakage inductance and the primary side clamp capacitor to achieve soft switching, eliminating switching losses, but the conduction loss is large, and the output rectifier has current oscillation. In order to solve the above problems, the best working mode of the converter is selected, the equivalent circuit model under different resonance modes is established, the influence of the resonance mode on the working state of the converter is analyzed in depth, and the experimental prototype is made based on the secondary side resonance mode. The experimental results show that the secondary side resonant active clamp flyback converter can realize the soft switching of power devices, reduce the rms value of the primary current, eliminate the phenomenon of secondary side current oscillation, and the maximum full load efficiency of the designed converter reaches 94.06%, and the efficiency of the whole machine is higher than that of the primary side resonance mode.

The new power system with renewable energy generation as the main body has brought new challenges to the system dispatching. A stochastic unit commitment model considering wind power as the operating reserve is proposed to alleviate the reserve pressure brought by the integration of large-scale renewable energy. Firstly, the probability density estimation of wind power prediction error is obtained based on the kernel density method, and the wind power reserve model is established according to the best confidence level. Secondly, we propose an all-scenario-feasible dispatching model based on the vertex scenarios with variable uncertainty sets and introduce strong nonanticipative constraints to meet the nonanticipativity of economic dispatching. Finally, in the improved IEEE-24 bus system, the effectiveness of the proposed stochastic unit commitment model is verified by the actual data and is compared with the scenario-based two-stage stochastic optimization. The experimental results show that the proposed model has satisfactory performance, can overcome the defects of numerical scenarios and large computing scale in stochastic optimization, and effectively reduces calculating time.

When the virtual synchronous generator (VSG) is connected to the grid, there is coupling between the steady-state performance and dynamic performance of the output power, which cannot meet the demand of suppressing active oscillation and primary frequency modulation of the grid at the same time. A control strategy based on angular frequency transient feedforward was proposed. This control strategy reduces Δω by compensating the output power, which in turn reduces the oscillation process. This control strategy can effectively suppress the generation of active oscillations, and realize the decoupling between steady state performance and dynamic performance, which does not affect the characteristics of primary frequency modulation, and improves the response speed. First, VSG active closed-loop small signal model is established, the contradiction between steady state and dynamic performance of output power is analyzed, and the active power oscillation mechanism is analyzed according to the power angle characteristics of synchronous generator. On this basis, a control strategy based on angular frequency transient feed-forward is proposed, and the influence of the proposed control strategy on the system is analyzed by using closed-loop zero-pole and Bode diagrams. Finally, the feasibility and superiority of the proposed control strategy are verified by simulation and RT-LAB HIL platform.

The coupling operation of dual-motor system needs to be considered in the optimal design of dual-motor. In the traditional optimization methods, the method of estimating efficiency Map is often used to obtain the optimal torque distribution coefficient of the dual-motor system. However, the error caused by the estimation method cannot be ignored in the optimal design of high-efficiency motor. In addition, the control strategies of the motor are also different under different working conditions. In order to improve the operating efficiency of dual-motor drive system under all operating conditions, based on two kinds of driving cycles, a collaborative optimization design method of dual-motor for electric vehicle is systematically proposed in this paper. Firstly, the parameters of the primary motor are obtained by parameter matching, and then the Map calculation method of motor efficiency based on semi-analytical model is proposed. Based on this method, the optimal torque distribution and control strategy of dual-motor system under different working conditions are studied. Then based on the particle swarm optimization algorithm, considering the control strategy of the motor under different operating conditions, the parameters of the dual motor are optimized under all working conditions. Finally, a hardware-in-the-loop experimental platform is built. Simulation and experimental results show that the proposed optimization method can improve the operation efficiency of the dual-motor drive system.

Photovoltaic power generation system has different fault response characteristics from synchronous machine, which brings severe challenges to power grid fault protection and control. The output of the phase-locked loop of the photovoltaic power generation system directly affects the fault response characteristics of the photovoltaic system, especially the non-periodic transient response deviation of the output of the phase-locked loop caused by the voltage phase jump after the grid fault, which has a great impact on the short-circuit current. The existing studies ignore the phase-locked transient process or assume that the phase-locked deviation is constant, which may cause large errors in the analytical calculation of photovoltaic short-circuit current. For this reason, in the present paper the expression of the deviation between the output phase of the photovoltaic phase-locked loop and the voltage phase of the grid-connected point is derived, the time-domain variation characteristics of the phase-locked deviation and its influencing factors are analyzed, and the influence of the phase-locked deviation on the three-phase short-circuit current of the photovoltaic power generation system is analyzed, thus the analytical calculation method of the three-phase short-circuit current of the photovoltaic power generation system considering the transient response of the phase-locked loop is proposed, and the characteristics of the short-circuit current are analyzed, Finally, the simulation model of photovoltaic grid-connected system is built to verify the correctness of the theoretical analysis.

Accurate parameter identification of synchronous generators is an important foundation for ensuring transient stability analysis of power systems. Firstly, based on the equivalent mathematical model, sequence network diagram and equivalent circuit of synchronous generator, the expression of transient current under the condition of phase to phase short circuit fault through external impedance is derived. Then, using short-circuit tests and identification to obtain the minimum objective function of the square sum of standardized errors between short-circuit currents, an improved whale optimization algorithm with increased weight coefficients is adopted to propose a parameter identification method for synchronous generators based on phase to phase short-circuit fault currents. Finally, a short-circuit test was conducted on an actual synchronous generator to verify the correctness and effectiveness of the proposed method. The method in this paper improves the accuracy of identification by increasing the excitation energy of synchronous generator and using the fault current in the process of large disturbance as the original data. At the same time, combining the nonlinear characteristics of the short-circuit current model, the whale optimization algorithm is improved to better adapt to nonlinear parameter identification.

In extreme weather conditions, network reconfiguration and island partition are important means for fault recovery of distribution networks with distributed generations. According to the development process of meteorological disasters, the multi-period fault recovery strategy is conducive to improving the resilience of distribution network. The existing fault recovery strategies do not consider the operation cost of multiple network reconfigurations and island partitions, as well as the fluctuation of distributed power supply in the island, resulting in poor security and economic results of the optimization results. Therefore, this paper proposed a multi-period recovery strategy for improving distribution network resilience during extreme weather conditions. By constructing a unified model of active distribution network reconfiguration and island partition, considering the recovery time scale under different fault causes, and subdividing the time section, the strategy can realize the dynamic adjustment of distribution network structure during the fault duration, and improve the resilience of the power grid. Finally, the proposed strategy is verified in the IEEE 33-bus system. The case shows that the proposed strategy has fewer switching operations and higher load recovery rate; and it can resist power disturbances within a certain range, which can improve the resilience of the distribution network in extreme weather conditions.

Enhancing the rotational inertia level of the wind power grid-connected system through the coordinated control of the wind-storage combined system (WSCS) is an important means to enhance the frequency stability of the system. The coupling degree of WSCS is low, and it is difficult to give full play to the response and adjustment capabilities of wind power and energy storage to frequency disturbances. In this regard, this paper proposes a coordinated control strategy for the WSCS based on the Linear Quadratic Regulator (LQR). This strategy takes the output frequency of the DFIG and the total output power of the WSCS as the control input of the energy storage to improve the damping and stability of the system and enhance the frequency response adjustment capability of the system. Firstly, according to the state equation of the system, the small-signal stability model of the DFIG and the WSCS is established, and the effect of coordinated control on the damping ratio of WSCS is analyzed. On this basis, the energy storage power capacity is determined according to the maximum rotor kinetic energy released by the synchronous generator. Finally, the grid-connected model of the WSCS is built in Matlab/Simulink, which verifies the effectiveness and superiority of the strategy.

In electric vehicle wireless power transfer systems, realizing efficient transmission while reducing magnetic leakage has been a technical challenge. To address this issue, the paper proposes a sunken shielding coil structure applied to a multi-radio wireless power transfer system, which reduces the magnetic leakage from the target surface without affecting the transmission efficiency of the system. Firstly, a method of calculating the magnetic field of a rectangular coil based on the vector magnetic potential is submitted, by which the magnetic leakage from the target surface of the system is analyzed, providing a theoretical basis for the subsequent magnetic leakage optimization; secondly, a method of magnetic leakage optimization is introduced, and each coil parameter meeting the requirements is obtained by applying the method, which provides a key support for the realization of high-efficiency wireless power transfer; lastly, a set of dual-sunken shielded coil structures with magnetic shielding structure is developed based on the coil parameters obtained; and lastly, a set of dual-sunken shielding coil structures with magnetic shielding structure applied to multiple wireless power transfer systems is developed based on the coil parameters obtained, which will not impact the system transmission efficiency. Finally, based on the obtained coil parameters, a dual-position electric vehicle wireless charging system with magnetic shielding structure is developed, and the effectiveness of the proposed shielding structure and method is fully confirmed through simulation and experiment. The results show that the proposed shielding structure not only reduces the maximum leakage magnetic field in the target area by 25% but also achieves a transmission efficiency of up to 95% when the output power of the system is constant at 4 kW.

In recent years, the distribution network resilience enhancement technology developed in response to extreme events has developed rapidly. However, in practical applications, the high economic cost of technical solutions is one of the important factors restricting its implementation. Based on the above problems, this paper proposes an economic post-disaster restoration decision-making method for resilient distribution network with MESS and electric vehicle V2G, which reduces the economic cost of restoration while ensuring the restoration effect. In the pre-disaster stage, a pre-disaster electric vehicle scheduling model is established to obtain the distribution of electric vehicles and the maximum output of each V2G station. According to the actual line layout and load information, the MESS temporary warehouse deployment location is determined. In the post-disaster stage, the comprehensive economic cost of post-disaster restoration is taken as the objective function to optimize the V2G station output and MESS scheduling in the restoration process. The proposed method is verified by multiple sets of examples. The simulation results show that the proposed collaborative restoration scheme can effectively improve the economy of the resilient strategy while reducing the post-disaster power loss of the system.

As more and more renewable energy resources are connected to the grid through power converters, the inertia of the power system is decreasing. At the same time, a large number of induction motors on the load side can provide frequency support and improve frequency response dynamics. However, accurate modeling of such a large number of induction motors requires detailed parameters and heavy computational cost. To address the limitation, a data-driven model for system frequency response is proposed. By collecting historical data of system frequency response, the identification of the equivalent inertia and damping coefficient of the power grid is described as an optimization problem. The objective is to minimize the frequency difference between the model and historical data。A heuristic algorithm is adopted to solve the problem efficiently. Compared with the mechanism model, the proposed dynamic equivalent model is structurally simple and does not require detailed parameters of induction motors. Simulations on a modified IEEE 9 bus system verify the effectiveness of the proposed method. The results also show that the induction motor load, which has a self-inertia of 15 seconds and accounts for 22% of the load side, provides 9% equivalent inertia to the system.

There is lots of rotational magnetic flux in transformer cores or motor cores. The hysteresis and magnetostrictive properties of silicon steels of core under rotational magnetization will increase the core loss and vibration deformation. In order to model the coupled hysteresis and magnetostrictive properties in the core silicon steel effectively, based on experimental data, this paper proposes that the eddy current loss and abnormal loss of electrical steel sheet under rotational magnetization are introduced into the energy balance formula of traditional Jiles-Atherton hysteresis model to characterize the rotational hysteresis characteristics of electrical steel sheet. At the same time, based on the nonlinear loop curve relationship between magnetostriction and magnetization, the first-order inertial magnetostrictive model under rotational magnetization is established. The magnetization intensity characterized by the hysteresis model is mapped to the magnetostrictive model, and the coupling relationship between hysteresis and magnetostrictive characteristics is established. Finally, the effectiveness of the proposed model is verified by experiment. The results show that the proposed coupling model can effectively characterize the rotational magnetic properties of electrical steel sheets, and provide a reference for the optimization design of high-quality electrical products.

This paper analyzes the topology, parameter design and control strategy of the distributed DC chopper and improves its control strategy. By comparing the response curves of the traditional DC chopper, the distributed DC chopper and the distributed DC chopper with the improved control strategy, it is shown that the distributed DC chopper with the improved control strategy has a smooth energy consumption curve and better fault ride-through (FRT) performance. On this basis, to address the problem of high cost of DC chopper with traditional FRT strategy, the AC-voltage magnitude reduction method is designed based on the permanent magnet direct-drive wind turbine to actively reduce the output power of the wind farm when a fault occurs, and the FRT coordination control strategy is designed in combination with the distributed DC chopper using the improved control strategy, which can significantly reduce the capacity of DC chopper and the cost of system while ensuring FRT performance of system. Based on the actual parameters of the Rudong offshore wind via VSC-HVDC project, the effectiveness of the proposed coordinated control strategy is verified by establishing the system model in the PSCAD/EMTDC.

Energy storage plays an extremely important role in the field of renewable energy consumption. Large-scale construction of energy storage will help promotion of the integration of renewable energy into the power system and help to achieve the "dual carbon" goal. However, the investment and construction cost of energy storage is relatively high, and careless allocation of energy storage will lead to a large waste of funds. Therefore, it is necessary to study the optimal allocation method of energy storage for renewable energy consumption, taking into account of both the consumption effect of renewable energy and the investment funds. This paper proposes a two-stage energy storage optimization method. In the first stage, the operation simulation of the power system is performed to determine the optimal energy storage type selection scheme. In the second stage, a dual-objective optimization model to minimize the investment cost and the curtailment of wind and solar power is constructed, and the model is solved to obtain a realistic energy storage schedule scheme. The case study analysis shows that the proposed method in this paper can greatly increase the consumption of renewable energy and reduce the investment cost.

In this paper, a wide-area damping control strategy and corresponding design scheme is proposed such that grid-connected converters can be used to improve the small signal rotor angle stability of the system. Based on the small signal stability model of power system with grid-connected converters, the modal linear quadratic regulator (MLQR) is applied to design the state feedback control strategy, which can achieve the decoupling control of different rotor angle oscillation modes. Considering that different grid-connected converters have different regulation capabilities, this paper further builds a damping effort allocation model, which can be solved by using the genetic algorithm (GA). In the allocation model, the weight matrix of MLQR is regarded as the variable to be optimized, meanwhile the damping ratio of key oscillation modes and the regulation ability of grid-connected converters are used as constraints. Finally, simulation tests are carried out in the Power System Analysis Toolbox (PSAT) based on the IEEE 68 bus system, and the results show that the damping control scheme can effectively use each grid-connected converter to provide sufficient damping support to the system within their control capabilities.

Distribution network fault recovery depends on the looping operation, but the impulse current generated during the looping process may cause the line current to exceed the limit, which may not only damage the equipment, but also endanger personal safety. Currently, the suppression of closing current is mostly focused on the overall optimization, but not on the impact current generated by the closing transient process. In particular, there is a delay between the issuance of the closing command and the actual closing of the loop in the distribution center, which will directly affect the size of the closing ring impulse current. The existing methods assume that the closing operation is completed immediately, ignoring the delay of the closing ring, and that may further cause the suppression of the closing ring impulse current to fail to achieve the expected goal. For this reason, a method considering the synergistic suppression of the closing loop impulse current by the closing loop delay and DG control is presented. By analyzing the generation process and principle of closed-loop impulse current in distribution network, the influence of DG output and closing delay on closed-loop impulse current is depicted, and a control optimization model of DG active control and closing-loop cooperation is established. A collaborative control method for closed-loop impulse current in distribution network with distributed power supply considering closing delay is presented. The example shows that this method can minimize the closing impulse current during the recovery process of distribution network and improve the safety of distribution system by optimizing DG output and the expected closing time.

Gas Insulated Switchgear (GIS) is an important substation equipment in the power system. If it fails, it will bring serious losses to the national economy. GIS equipment is subjected to not only power frequency operating voltage during operation, but also to transient impulse voltage. Large transient surges can trigger small defects hidden under power frequency operating voltage to generate partial discharge. Focusing on the partial discharge signal under the surge voltage can effectively improve the sensitivity of detecting small defects inside the equipment. In response to this, this article sets up typical insulation defects on physical GIS, and based on optoelectronic integrated fusion sensors, uses ultra-high frequency method and optical measurement method to measure and analyze partial discharge under oscillating impulse voltage. The partial discharge detection results of three typical defects in physical GIS under oscillatory impact indicate that the discharge under sharp defects mainly occurs near the peak of applied voltage. But when the voltage is high, due to the influence of the reverse electric field formed by the space charge, the valley discharge is triggered. The discharge under suspended defects will occur in more discharge cycles, mainly at the rising and falling edges of the applied voltage. Some of the discharge amplitudes are larger, and the ultra-high frequency method and fluorescent fiber method can simultaneously detect the discharge pulse. The discharge pulses under surface defects occur sequentially at the rising and falling edges of the applied voltage, and the fluorescence fiber method can only detect very few discharge pulses.

The influence of modular combined stator structure with centralized winding on the performance of low speed and high power direct drive permanent magnet motor is studied. At first, the modular rule and modular number of the modular stator are analysed.The winding function and inductance expressions of a single stator unit module with different modular modes are derived based on the winding function method. Based on the finite element simulation, the influence of modular winding on motor performance is analyzed firstly, and then the influece of modular winding and modular stator core on motor performance is analyzed. By comparing the no-load and on-load performance, the advantages and disadvantages of different modular modes are summarized, which establishes a foundation for the modular design and manufacturing of high-power and low-speed direct-drive permant magnet synchronous motor.

In order to improve the problem of magnetic field leakage in wireless energy transmission systems, this paper proposes a strongly coupled active magnetic shielding structure based on passive capacitive shielding. Firstly, a strongly coupled active magnetic shielding coil structure is designed on the basis of passive capacitive shielding of wireless energy transmission system. Secondly, the operating principle and design method of this coil are given, and the mathematical model as well as the equivalent circuit model are derived. The principles of capacitive shielding and active shielding are explained theoretically, and the shielding effect and transmission efficiency are analyzed as affected by the variation of shielding coil parameters. Finally, a wireless charging system for electric vehicles is designed on the basis of the proposed coil structure by combining the obtained coil parameters, and the effectiveness of the proposed coil structure and method is verified through theoretical calculations, simulations and experiments. The results show that the coil structure is able to reduce the magnetic leakage of the system by about 40% while maintaining a transmission efficiency of more than 96%, which realizes the goals of reducing the leakage magnetic field and maintaining a high transmission efficiency.

Commutation failure is a unique fault of LCC-HVDC, which is particularly conspicuous in weak AC systems. This paper firstly analyzes the reasons for LCC commutation failure, and then proposes a hybrid commutation converter technology scheme that applies high-power controllable shutdown IGCTs for thyristor replacement. And combined with characteristics of IGCT, active shutdown strategies and implementation methods for HCC are proposed，under the conditions of normal commutation and commutation failure resistance. Subsequently, according to the actual HVDC control and protection framework, the primary circuit, CCP and PPR systems of HCC system in the RTDS environment were designed and established, for what only the active shutdown part was added compared to LCC. Finally, a series of experiments were conducted to verify the feasibility and accuracy of the HCC system for resisting commutation failure.

With the expansion of the scale of the modular multilevel converter (MMC) based high voltage DC power grid, the short-circuit current presents the characteristics of fast rising rate and large peak value at the initial stage of the DC shortcircuit fault. These new features severely limit the development of HVDC power grid. In order to quantitatively evaluate the short-circuit current at the DC side of MMC-HVDC power grid, a quantitative evaluation index of short-circuit current at the initial fault stage of MMC-HVDC power grid is established from the perspective of the inherent characteristics of the system to guide the planning and operation of DC power grid. Firstly, a short-circuit current calculation method based on MMCs’ input-output characteristics is proposed. This provides theoretical support for the quantitative assessment of short-circuit current. Secondly, the pole-to-pole short-circuit current of DC power grid is decoupled, and the quantitative evaluation indices of the initial stage short-circuit current are established from the perspective of system inherent characteristics. Finally, the proposed decoupling short-circuit current calculation method and quantitative indices are verified in DC power grid with different parameters and structures. The verification results show that the proposed index can effectively evaluate the short-circuit current of MMC-HVDC power grid without calculating the short-circuit current, and can guide the planning of DC power grid, the formulation of operation mode and the selection of system parameters.

To alleviate the problem of electric vehicle owners’ mileage anxiety, this paper proposes a hybrid filter and neural network-based state of charge (SOC) estimation method for electric vehicles, which can accurately estimate the SOC and remaining mileage of electric vehicles. Firstly, a dimensionality reduction algorithm and a classification algorithm are used to isolate five categories of driving behaviors that reflect vehicle energy consumption from the real vehicle dataset as part of the model input. Secondly, a hybrid model combining Kalman filtering and a two-layer bi-directional long short term memory neural network is built, which can reduce the noise of real-time data and combine with historical data to calculate EV SOC and remaining mileage. Finally, different model input features and model structures are compared to demonstrate the high accuracy of the proposed method.

Due to the randomness and volatility of wind and photovoltaic power generation, and the more complicated structure of the distribution network after being connected, the reliability of power supply of the distribution network is reduced. This paper proposes a distribution network reconstruction scheme combining the quasi-Newton genetic algorithm with robust optimization to address this issue. Firstly, based on the output model of wind and photovoltaic power generation, probability multi-scenarios are generated. Secondly, a robust reconstruction optimization model of the distribution network with wind and photovoltaic power generation access is established, and the quasi-Newton genetic algorithm is used to solve the model. The risk value of voltage out of limit in the distribution network before and after reconstruction is compared. Finally, an example is given to verify that the reconstruction method in this paper can effectively improve the reliability of power supply of the distribution network.

Increasing of temperature will affect the hysteresis characteristics of magnetic materials, and then altering the performance of electrical equipment. At present, the Preisach model cannot effectively characterize temperature, resulting in significant errors in loss calculation results. Therefore, the degree to which the characteristic parameters of the analytical Preisach model based on the Lorentzian function will affect the shape parameters of the hysteresis loop, such as saturation magnetic density, coercive force, residual magnetism is firstly analyzed in this paper. The changes in model parameters and material magnetic properties at different temperatures are studied. Based on the shape correlation and temperature correlation of the hysteresis loop of the model characteristic parameters, a temperature coefficient is introduced to correct the model characteristic parameters, and an analytical Preisach model is constructed under variable temperature conditions. A method for identifying the model parameters considering the influence of temperature is also provided. The final experiment measures the ultimate hysteresis loop of nanocrystalline alloys under variable temperature conditions. After comparing multiple sets of measured values with the corrected analytical Preisach model calculation values, it can be found that the average relative errors of the corrected model results at saturation magnetic density, coercivity, and remanence are 0.15%, 2.21%, and 5.76%, respectively, proving the accuracy of the corrected model.

Natural ester insulating oil has been widely used in distribution transformers because of its high ignition point, green environmental protection characteristics, and its main physical and chemical electrical properties can meet the requirements of power oil. However, compared with mineral insulating oil, natural ester has problems such as high kinematic viscosity, high pour point and poor oxidation stability, which limits its application environment. In view of the above problems, this study evaluated the antioxidant activity of several common antioxidants, tested the influence of antioxidants on the oxidation stability and dielectric properties of mixed ester insulating oil, and carried out compound experiments to evaluate the application effect of antioxidants in insulating oil in advance, and provided a basis for the selection of antioxidants in mixed oil. This study provides some theoretical guidance for the development and performance improvement of ester insulating oil.

As the penetration rate of photovoltaic power generation increases, the uncertainty of its output has negative impact on safe and stable operation of the power grid. By utilizing the mobile energy supply characteristics of electric vehicle (EV), the collaborative optimization between EV and photovoltaic can be realized. Taking the flexibility of EV energy scheduling into account, a two-stage optimal scheduling model for EVs considering user charging demand is constructed: in the day-ahead stage, a multi-objective optimization function with minimum situ absorption deviation of photovoltaic, maximum EV charging completion rate and minimum EV users travel cost is established, the charging and discharge coefficient is introduced to optimize the charging behavior of the EV; in real-time scheduling, the load aggregator combines the actual photovoltaic output of each period and the charging demand of the EV, modifies the optimized charging and discharging coefficients according to the scheduling priority to formulate an optimal charging and discharging strategy. By comprehensively considering the different needs of EV users for charging completion and charging cost, analyzing different charging modes and different weight coefficients, and considering the situation of users changing charging requirements, it is verified that the strategies proposed in this paper have obvious effects in reducing the deviation of photovoltaic absorption and meeting users’ charging needs.

DC bus is the main route of photovoltaic system output energy. Due to long-term exposure, weathering and other effects, cables, connectors and other components deteriorate, so the possibility of arcing in the DC bus of photovoltaic system rises sharply, and is easy to cause fire, electric shock and other accidents. In photovoltaic systems, series arc faults will cause the loop current to drop, which can not be recognized by conventional overcurrent protection. Therefore, this paper proposes a method based on deep learning and Dempster-Shafer (D-S) to identify series arc faults, which uses a one-dimensional convolutional neural network (1DCNN) to identify the arc of the detection data based on the current and voltage signals of shunt capacitors. On this basis, the recognition result based on a single sensing data is used as the evidence, and the reliability distribution is calculated by using the D-S multi-information synthesis rule, and finally the decision rule is used to determine whether a series arc fault occurs. The results show that the accuracy of series arc recognition based on current and voltage signals of shunt capacitors is 9719% and 9498%, respectively, while the recognition accuracy of DC series arc fault detection of photovoltaic system based on 1DCNN and D-S multi-information fusion can be increased to more than 99%.

In the automatic inspection of UAV, route planning should be carried out according to the position of insulator strings in the dot cloud of power corridor. Due to the large length span of the power corridor and the large number of poles and towers, it is a huge workload to manually mark the position of insulator string. At the same time, the point cloud data is scattered and disordered, and it takes a long time to locate insulator string directly in three-dimensional space. Therefore, this paper proposes a multi-view two-dimensional projection to rapidly extract insulator strings from three-dimensional pole and tower point clouds. Firstly, the robust principal component analysis was used to analyze the horizontal direction of the cross arm at the top of the tower in the top view, and the orientation of the point cloud of the tower was unified. Then, in the side view, the height of the power line is quickly located by Hoff line detection. According to the spatial relationship between the power line and the cross arm, the corresponding insulator strings are divided into three categories: Top suspension, vertical insulator string and horizontal insulator string. Finally, the corner detection is carried out in the multi-view projection, and the connection endpoint of the insulator string with the power line and the tower is located to realize the rapid extraction of the insulator string. The method proposed in this paper was used to extract 867 insulator strings from 97 different types of pylons in a 50 km power corridor. It is proved that the method can extract different types of insulator strings quickly.

To address the problem of low accuracy of transformer fault diagnosis, a multi-strategy improved whale optimization algorithm (MIWOA) is proposed to optimize the transformer fault diagnosis model of stochastic configuration network (SCN). First, the raw transformer redundant and extensive fault data are subjected to kernel principal component analysis (KPCA) to reduce the influence of invalid features. Secondly, the whale optimization algorithm (WOA) is improved by using tent chaos mapping, dynamic adaptive weighting and primary knowledge acquisition sharing algorithm to improve its optimization capability. Then, the L2 parametric penalty term is introduced in the SCN for regularization and the improved MIWOA algorithm solves the SCN penalty term coefficients C in an optimal way to improve the SCN classification accuracy and generalization ability. Finally, in order to accelerate the convergence speed of the model, degraded data are input into the MIWOA-SCN fault diagnosis model. The results show that the diagnostic accuracy of the model is 93.1%, which is 6.89% and 9.48% higher than the WOA-SCN, GWO-SCN, and PSO-SCN diagnostic models, respectively. This is 14.65% higher. This proves that the MIWOA-SCN diagnostic model has good diagnostic performance for transformer fault diagnosis.

Due to the large uncertainty in the measurement results of the National Standard Epstein method to measure the specific total loss of the new-level energy efficiency low loss thin silicon steel sheet, this paper proposes a new method based on double-Epstein for measuring the specific total loss of loss thin silicon steel sheet. Using the double-Epstein method the specific total loss of the silicon steel sheet is measured, and the errors existing in the measurement method are analyzed and corrected. By processing the error-corrected experimental data the loss separation between the joint area and the uniform area of the Epstein is realized, and the mechanism of the total loss in the joint area on the measurement results of the Epstein is analyzed. The finite element simulation model of the Epstein is established, and study the range of the influence area of the joint and the loss of the uniform area and the joint area is studied. The simulation results are consistent with the measurement results of the double Epstein, which verifies the effectiveness and accuracy of the double-Epstein. The measurement and simulation results show that the results of measuring the specific total loss of thin silicon steel sheets by double Epstein method have higher accuracy than those measured by the Epstein method. The measurement method and error correction method proposed in this paper can be used for more accurate measurement of the magnetic properties of the first-class energy efficient thin silicon steel sheet.

Real-time online monitoring of temperature along power cables can effectively avoid the occurrence or expansion of cable fires. Distributed fiber optic temperature sensing technology has been widely used in cable temperature monitoring by virtue of its advantages of anti-electromagnetic interference and high temperature resistance. However, the signal-to-noise ratio of temperature signals decreases with the growth of distance when distributed temperature measurement is performed on long-distance power cables, which affects the accuracy of cable temperature measurement. To address this problem, a noise reduction method based on convolutional neural network is designed in this paper, and a large number of a priori data sets are used to train the neural network noise elimination model, which is applied to the long-distance distributed temperature measurement signal for noise filtering. The experimental results show that the noise reduction method in this paper can suppress the noise level of the distributed temperature measurement signal with a length of 11 km from the original ±175 ℃ to within ±1 ℃, effectively suppressing the noise and improving the accuracy of temperature measurement.

With the development of hydro-generators towards large capacity and high speed, higher requirements have been imposed on rotor cooling technology. Evaporative cooling technology is an efficient cooling method that relies on the heat absorption during the phase transition of the cooling medium. However, current evaporative cooling rotor schemes require a certain amount of liquid cooling medium to be stored on the rotor. In order to investigate the relationship between the liquid cooling medium on the evaporative cooling rotor and the rotor vibration characteristics, this paper preliminarily establishes a pipe-cooled evaporative cooling structure based on a prototype model of a vertical hydro-generator. The influence of evaporative cooling medium on the natural frequency of the rotor at different liquid level heights was studied. The results show that with the increase of liquid level height, the pressure of the cooling medium on the pipe wall gradually increases, and there is no significant effect on the natural frequency of the rotor itself. The work presented in this paper provides certain guidance for subsequent optimization of the evaporative cooling structure of rotors, as well as further research on the coupling relationship between liquid cooling medium and rotor vibration characteristics.

In broadband voltage measurement, transient overvoltage components will seriously affect line power quality and power system security. The traditional measurement method often uses a single microprocessor to process data. It is difficult to realize the real-time and synchronization of multi-channel high-speed data acquisition. It cannot realize the acquisition of transient overvoltage signals and cannot meet the requirements of broadband voltage measurement. The voltage measurement system designed in this paper uses the advantages of fast operation speed, low internal delay, hardware parallel processing of FPGA and rich ARM communication interface, many peripheral resources and strong control ability to realize high-speed conditioning acquisition, processing and transmission of broadband voltage signals. In the data input layer, edge nodes are introduced to perform data pre-screening, which solves the problem that the cloud pressure in data processing is large and it is difficult to achieve real-time data evaluation, thereby improving the efficiency of data transmission.

As an electromechanical energy conversion device, motors are widely used in electric vehicles, aerospace, energy metallurgy and other fields, but their operating scenarios vary widely. In order to adapt to the operating characteristics of the load under different scenarios and working conditions, the motor usually needs to have a certain torque overload operation ability. Accurate analysis and utilization of the torque overload capacity of the motor is of great significance to improve the economy of the system and realize energy saving and consumption reduction. This paper firstly introduces the motor torque overload capacity and utilization methods, and summarizes the application scenarios and practical value of high torque overload capacity motors. The electromagnetic characteristics, loss characteristics and temperature limit of motor torque overload operation are analyzed. The constraint conditions and utilization boundary of motor design with high torque overload capacity are summarized. The research status of permanent magnet synchronous motor and asynchronous motor with high torque overload capacity is analyzed and summarized respectively, and the strategies to improve the torque overload capacity of the motor are sorted out. Finally, the development direction of research and utilization of high torque overload capacity motor is prospected.

Offshore wind power is an important trend for the development and utilization of new energy. The rational planning of offshore wind power systems has an important impact on the operating economy and safety of the system. The planning and evaluation of the existing offshore wind power system is difficult to balance the power quality of the offshore wind farm side and the operational safety of the transmission system side, and cannot comprehensively reflect the performance of the offshore wind power system. Therefore, the differences between the power quality of wind farms and the fault characteristics of transmission systems caused by different planning schemes of offshore wind power systems are analyzed, the inferior evaluation indicators of offshore wind farms and transmission systems are established, and the differences and correlations between the indicators are fully considered, and then a TOPSIS comprehensive evaluation method of offshore wind power system is proposed to improve the CRITIC entropy weight combination weighting method, and is practical in combination with the early planning and design of an offshore wind power system. The results show that the proposed comprehensive evaluation method is consistent with the actual situation, and has reference value for the planning and decision-making of offshore wind power system.

In view of the carbon peaking and carbon neutralization goals, this paper proposes a net-zero carbon emission day-ahead optimal scheduling method for the isolated integrated energy system based on the hydrogen-carbon coupling, to address the self-sufficiency and low-carbon energy supply of the isolated integrated energy system (IIES). First, the amount of substance and energy balance principles is applied to analyze the cycle of different kinds of energy and carbon atoms. The net-zero carbon emission operating mechanism is proposed based on hydrogen and carbon. Then, a net-zero carbon emission day-ahead optimal scheduling model for IIES is established. The daily total cost of IIES is minimized in the optimization model, and the net-zero carbon emission mechanism, operation of power system and natural gas systems are considered by constraints. The model was transformed into a mixed integer linear programming problem. Finally, a simulation is implemented by using IEEE 39-NGS20 electric-gas interconnection system. The simulation results show that the proposed method achieves 100% self-sufficiency and net-zero carbon emission operation of the system, and significantly improves the economy of the day-ahead scheduling of the IIES.

With the increasing complexity of power grid interconnection, thermal stability has become the main factor limiting power transmission capacity. Especially in the case of transmission lines passing through loads, the existing methods ignore the dynamic thermal characteristics caused by line power changes, resulting in errors in the calculation of line thermal stability safety margin, which may lead to premature protection action and line removal, or even threaten the safe and stable operation of the entire power system. Therefore, the factors affecting the temperature rise of transmission lines are analyzed, and the sensitivity model between unit operation mode, power regulation and overload line power is established. Combined with the dynamic thermal balance equation of the line, a method for calculating the thermal stability safety margin of overload lines considering the power change is proposed. The numerical example in this paper shows that the method fully considers the influence of power variation of overloaded line on thermal stability, and can maximize the delay of protection action while ensuring the safe operation of transmission line, so as to reduce the scope of outage and chain fault.