The three-core underground cable in the distribution network works in a harsh environment. Due to the influence of aging，external force，high temperature and humidity，the insulation of long-term live operation is easily damaged and causes faults. Aiming at the single-phase grounding fault of cable in distribution network，a fault location method based on the refraction-reflection characteristics of traveling wave head was proposed. Firstly，the zero-mode voltage of each line was obtained，and the arrival time of the wave head was determined. The waveform in a power frequency period after the arrival of the wave head was selected，and the main frequency of the wave head was determined. The square wave with the same frequency as the main frequency of the wave head was selected as the initial traveling wave signal，and the attenuation signal waveform at the head and end of the initial traveling wave signal after refraction of different times at this frequency was calculated.If the correlation between the corresponding data of the waveform calculated at both ends met the requirements，it was assumed that the fault point is the actual fault point. Otherwise，continue to narrow the fault interval until the correlation between the waveform data is satisfied. Simulation results show that the method can quickly and accurately realize fault distance measurement，reduce the complexity of fault distance measurement，and has strong effectiveness and practicability.

The accurate identification of hidden danger for power utilization in low-voltage substations plays an important role in improving the quality of power supply and reducing the risk of accidents.To improve the accuracy of identifying hidden danger in low-voltage substations，a low-voltage user hidden danger for power utilization identification model based on SSAE-SSA-GRU was proposed. Firstly，the user's original voltage data was normalized，and the feature parameters of the data were extracted through a stacked spares auto-encoder（SSAE）to solve the redundancy problem caused by the high dimensionality of the original voltage data. Then，the sparrow search algorithm（SSA）was introduced to optimize the hyperparameters of the gated recurrent unit（GRU）network，improving the accuracy of the model's fault diagnosis results.Finally，the performance of the established SSAE-SSA-GRU model was evaluated through numerical examples，verifying the effectiveness of the proposed method in identifying hidden danger for power utilization for low-voltage users. Compared with traditional methods for identifying abnormal electricity usage，the proposed method has good convergence and high accuracy.

Incidents such as the burning of electromagnetic voltage transformers（PT），damage to primary harmonic suppressors，and fuse tripping occur frequently in low and medium voltage distribution systems due to ferroresonance，severely affecting the safe and stable operation of the system. Therefore，through theoretical analysis and combined with field case studies，it was verified that the saturation current produced by PT saturation due to electromagnetic transient impacts from system single-phase ground faults and circuit breaker operations was the main reason for the frequent fuse tripping. Secondly，the factors influencing the saturation current of PT was analyzed and the capacity of fuses to withstand the PT saturation current was tested. The research indicates that the probability of fuse tripping could be reduced by increasing the PT's DC resistance，choosing cylindrical harmonic suppressors with relatively high knee-point voltages of their volt-ampere characteristics，and increasing the rated current of the fuses. Finally，specific recommendations for the selection of PTs，harmonic suppressors，and fuses were provided，offering reference measures for resolving the issue of frequent fuse tripping in electromagnetic voltage transformers protected by fuses.

The common-mode equivalent circuit model of the motor is the basis for analyzing the electric erosion of bearings，especially for analyzing the technical problems and experimental phenomena of shaft voltage and shaft current，among which the centralized equivalent model is an important calculation basis for the key index of bearing electric erosion that is bearing voltage ratio （BVR），which can be evaluated in the early stage of motor design. The accurate simulation calculation of the distributed capacitance parameters of the centralized equivalent model were studied in depth. Firstly，the simulation calculation and comparison of the two-dimensional single-slot and full-model motors were carried out. Secondly，the influence of the stator winding end and the rotor end ring on the stray capacitance was considered，and the three-dimensional motor model was simulated and calculated，and the more accurate distributed capacitance parameters were obtained through comparative study. Finally，the parameters of YQ190-14 type traction motor were taken as an example，and the simulation calculation results and test results were compared and analyzed，and the accuracy of the simulation calculation results was verified.

A backstepping error port-controlled Hamiltonian （EPH） controller based on a novel extended state observer （ESO） was designed to address the issues of insufficient rotor flux observation accuracy and slow system dynamic response in induction motor speed control. Firstly，an extended state observer was used to observe the rotor flux，expanding the change in rotor resistance in the model to a new state to improve the accuracy of rotor flux observation. Secondly，using the backstepping control method to obtain the balance point of the stator current of the EPH controller，designing a backstepping EPH controller can effectively improve the dynamic response ability of the EPH control. The experimental results demonstrate that the designed controller has better stability performance and faster response speed compared to the EPH controller.

Wind turbine condition monitoring and wind power prediction both rely heavily on power curves. Firstly，to increase the modeling accuracy of wind turbine power curves，the random forest technique was used to screen the important variables that influence wind energy capture ability. Then，the screened variables were fed into the improved Gaussian process（GP） model，which improved computational efficiency. Finally，four separate metrics were used to evaluate the model's correctness，and the entropy weight approach was used to resolve any potential conflicts between the metrics，resulting in a comprehensive assessment metric that measured the quality of the power curve model. The suggested approach's effectiveness was validated using supervisory control and data acquisition （SCADA） data from a wind farm in the United Kingdom，and the findings reveal that the proposed method improves model accuracy when compared to the current six types of conventional methods.

In the background of a high proportion of new energy source connected to grid，the phenomenon of new energy interface inverters being connected to the grid through long-distance AC lines is becoming increasingly significant. The traditional vector controlled weak grid connected voltage source converter （VSC） based on phase locked loop （PLL） synchronization is prone to PLL synchronization instability. To improve the PLL synchronization stability of weakly connected VSC，an analytical model to reveal the PLL synchronization instability mechanism of weakly connected VSC was established. Through theoretical analysis，the influence of the dynamic coupling characteristics of PLL and different time scale control links on the PLL synchronization instability mechanism was revealed. Based on the theoretical analysis results，a PLL dynamic compensation control strategy suitable for multiple time scales was designed to improve the PLL synchronization stability of weakly connected VSC. The simulation results based on Matlab/Simulink verify the correctness of the theoretical analysis and the effectiveness of the compensation control strategy.

In order to further improve the output performance and efficiency of the converter，a grid-connected converter based on heterogeneous device mixing was proposed，referred to as heterogeneous grid-connected converter（HGCC）. The HGCC consists of two half-bridge modules based on SiC MOSFET devices，which are cross-connected by the commutation bridge arm based on Si IGBT devices. Furthermore，the HGCC modulation principle was given. The SiC MOSFET device works in the high-frequency switching state，while the Si IGBT device works in the low-frequency switching state，giving full play to the advantages of low switching loss of SiC devices and low on-state loss of Si devices. Then，the working mode of HGCC was analyzed in detail，and the control block diagram of HGCC and the internal voltage balancing strategy of capacitor were given. Finally，the effectiveness and feasibility of the proposed topology and control strategy was verified by simulation.

Model predictive control （MPC） is an effective control strategy for permanent magnet synchronous generators （PMSG） due to its fast dynamic response and multi-objective optimization capabilities. However，MPC relies on accurate system models and sensor measurements. In practical conditions，parameter mismatch caused by PMSG parameter variations and sensor measurement noise can deteriorate the control performance of MPC. Robust predictive control based on extended state observer （ESO） can effectively deal with parameter mismatch. However，a single-gain ESO is difficult to balance parameter mismatch and measurement noise disturbance. Therefore，a robust predictive control method based on hybrid cascade parallel ESO （CPESO）was proposed，which used multiple sub-ESOs in series and parallel to weight system disturbances and observed values for noise suppression. This method can effectively balance parameter mismatch and measurement noise suppression. Finally，under conditions with parameter mismatch and measurement noise，experiments were conducted on a three-level PMSG test bench to verify the effectiveness of the proposed method.

In recent years，the use of microinverters has received a lot of attention as one of the viable methods for residential and commercial PV power conversion systems. Flyback inverters operating in current continuous conduction mode （CCM） have been widely studied for their low output ripple current，high efficiency，and low cost. However，its control duty cycle to output current transfer function has right-half-plane （RHP） zeros，which may cause system instability when the inverter is combined with a high-gain feedback controller. In addition，flyback CCM inverters are subject to grid time-varying voltage disturbances. As a result，the conventional control scheme leads to inaccurate output tracking. An interleaved flyback CCM microinverter iterative learning control （ILC）method was proposed to help the system output converge to the reference trajectory by utilizing the prediction term and the current learning term. Compared with the traditional PI control scheme，the system output globally converges to the reference trajectory without state disturbance，output noise and initial state error.