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.

The traditional technical line loss prediction method of low voltage station area has some problems，such as relatively extensive calculation，requiring underlying physical topology，and relying on influence characteristic data. In recent years，a technical line loss and meter error joint estimation technical route based on the principle of conservation of electric energy in station area has been formed，but there are still some problems of difficult model solving and long data requirement period. In order to achieve accurate estimation of technical line loss in low voltage station area，the correlation between daily technical line loss and energy supply was further analyzed on the basis of the existing joint estimation route，and the original model was optimized considering those users with small energy consumption have little influence on the model，and the technical line loss was solved based on gradient descending convex optimization algorithm. Finally，6 759 stations in a certain area were used to calculate the technical line loss. Compared with the traditional algorithm，the assignment accuracy of the proposed method reaches 98%，and is significantly improved.

Under the large-scale renewable energy integrated with uncertain output characteristics，balancing the supply and demand within a local area becomes a new challenge.The long-distance transmission and consumption scheme is utilized for the sending-end grid to meet the requirements of renewable energy consumption.Within the constraints of thermal stability，dynamically improving the transmission lines' rating capacity has become a critical method for the sending-end power grid.However，due to the insufficient thermal stability calculation model，the existing improvement methods have the problems of significant evaluation deviation and narrow applicability in the practical application of the sending-end power system the improvement scheme usually needs to be customized and modified for specific line. In order to solve above issues，firstly，the influence of dust corona heating on the thermal stability transfer capacity at the sending end was analyzed，and an improved model of line thermal rating based on the dust effect was proposed. Furthermore，considering the uncertainty of the dust effect，a calculation method of dust effect control parameters based on fuzzy analysis was proposed，and the thermal rate capability calculation model was improved. Finally，combined with the meteorological forecast，a scheme for improving the thermal rating capacity of the renewable energy transmission power grid was constructed，which can be analyzed for multiple lines simultaneously. Via the practical engineering case of the Ningxia power grid and the power meteorological forecast data of China Electric Power Research Institute，the effectiveness and applicability of the improvement model of dust effect and the improvement scheme of multi-line thermal stability transmission capacity were verified.

Accurate topology and line parameter information is the basis of state estimation and security control of distribution network. Affected by the performance of collection terminals and environmental factors，the measurement error of metering equipment often deviates from Gaussian distribution. Higher requirements are put forward for the robustness of topology and parameter identification model under non-Gaussian noise measurements.The mathematical optimization model of distribution network parameter identification was firstly constructed with the goal of minimizing power estimation error. In order to improve the performance of identification algorithm in complex error scenarios，the correntropy induced loss function was established，and an improved correntropy matching pursuit （CMP） algorithm was proposed based on half-quadratic optimization and noise filtering. Finally，the simulation analysis was carried out on IEEE 33- and 85-bus distribution system，and the test results show that the proposed method can correctly identify the topology and effectively estimate the line parameters in both Gaussian and non-Gaussian data noise scenarios.

The permanent magnet synchronous generator （PMSG） is prone to current overstep in unbalanced grid，which affects the reliability of grid-connected system. To solve this problem，low-voltage ride-throgh control strategy based on direct power control was proposed. In this strategy，the direct power inner loop was used to control the grid-side inverter，and the active power and reactive power instructions were divided into DC components and double frequency AC components. The reference values of the DC components of active power and reactive power were calculated on the premise of the low voltage traverse reactive power support and the current amplitude of the inverter. The reference values of the AC components of active power and reactive power were calculated according to three different control objectives according to the voltage and current of the junction point. Then the control loop was designed by the quasi-proportional resonant controller. Finally，a simulation model was built based on Matlab/Simulink，and the simulation results show that the proposed control strategy can improve the dynamic performance of the inverter and improve the operation ability of the grid-connected system under the unbalanced grid.