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.

Aiming at the problem of large switching loss of modular multilevel converter（MMC），starting from the switching frequency optimization strategy，the existing switching frequency optimization strategy was improved，and the accurate analytical formula of sub-module capacitor voltage based on the real-time value of MMC transmission power was derived，so as to calculate the fluctuation range of the mean value of capacitor voltage.The dynamic retention factor was obtained by using the margin between the mean value of capacitor voltage and the engineering constraint，and the final output switching instruction was realized by the main flow of the equalization strategy.The PSCAD/EMTDC model was built based on the offshore wind power flexible engineering parameters to verify and compare the proposed strategy with the traditional strategy.The simulation results show that under the premise of meeting the requirements of the project on the fluctuation range and the imbalance index，the switching frequency of the proposed strategy is reduced by 49%~58% compared with the traditional strategy under each steady-state condition，and the switching loss is reduced by 63%~90% under each steady-state condition，and the expected loss reduction effect is achieved.

In order to eliminate the problem of low inertia and large frequency fluctuation in wind power grid-connected system when power disturbance occurs，an improved virtual inertia control strategy was proposed.A cooperative control strategy of adaptive moment of inertia and damping coefficient was introduced in the main control system of wind power inverter. The energy storage static synchronous compensator（STATCOM/BESS）was used to provide the active power and reactive power required by the system. At the same time，the power output of STATCOM/BESS was adjusted according to the frequency deviation and change rate of the system. By analyzing the small signal model of virtual synchronous generator（VSG）of the fan，the setting rules of the adaptive VSG moment of inertia and damping coefficient were determined. The Matlab/Simulink simulation results show that the strategy has a more obvious effect on frequency fluctuation，and can effectively suppress the voltage drop of the fan junction point，and improve the ability of safe and stable operation of the system.

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 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.

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.

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.

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.

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.

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.