During the operation of high-voltage DC power grid，due to factors such as load characteristics and voltage fluctuations，the instantaneous power characteristics such as capacitor current and harmonics are more complex，which increases the difficulty of identifying faults in the power grid system. Therefore，a bipolar short circuit fault identification technology for high-voltage DC power grids considering instantaneous power characteristics was proposed. By establishing a topology model of the high-voltage DC power grid，the bipolar short circuit fault of the high-voltage DC power grid was anlyzed. Based on the instantaneous power charac-teristics of the endpoints of the high-voltage DC power grid，the area where the bipolar short circuit fault occurs was determined. Using the maximum value positioning method of dual terminal fault current to obtain bipolar short circuit fault location，the fault identification of bipolar short circuit in high-voltage DC power grid was completed. The experimental results show that the proposed method has high accuracy in locating and identifying bipolar short circuit faults in high-voltage DC power grids，and the efficiency of fault identification is improved.

After the distributed wind farm stations are integrated into the distribution network，due to the characteristics of wind farm short-circuit current amplitude control and frequency offset，the traditional three-stage current protection of distribution network is difficult to accurately identify the fault on the wind power transmission line. Based on the similarity of fault current traveling waves，a fast protection method for wind power transmission lines in distribution networks was proposed to ensure fast and safe operation of distribution networks. First，the differences in the supply fault currents at the two ends of the transmission line were analyzed. A similarity pilot protection approach was proposed by exploiting the difference in the current travelling waveforms during the initial phase of the fault. The wavelet mode maximum was used for the start of protection. With the improved longest common subsequence algorithm，the waveform similarity at both ends was measured for fault discrimination.Finally，the simulation results demonstrate the excellent speed and reliability of the proposed method.

Electrically assisted manufacturing （EAM）is a promising and rapidly developing metal processing method.The power supply is a key sub-system for EAM，which needs to be designed properly.the model-based design of a low-voltage high-current pulse power supply used for EAM was proposed based on converter-level electro-thermal modeling.The thermal stress of key components was obtained by converter-level finite element simulations.A simplified thermal modeling method was proposed to reduce the computation burden of the finite element modeling（FEM） simulation to obtain the dynamic thermal profile under pulse current operation.The impact of the duration of the current pulse on the maximum temperature and temperature variations of MOSFETs was investigated based on the thermal model.A case study of a 10 V/500 A pulse power supply was presented to demonstrate the theoretical analyses and verification. The outcomes contribute to the design optimization and virtual prototyping of pulse power supplies for EAM applications.

A bidirectional isolated resonant converter with variable mode and wide voltage range was proposed. The proposed converter has the advantages of BOOST circuit and flyback current feed topology. By reusing the pre-storage and flyback energy feedback of the resonant inductor，it can improve the gain from the battery side to grid side and the power density of the converter，while also reducing the current circulation. The converter adopts fixed frequency pulse width modulation and has multiple working modes，which is suitable for wide range output. the working principle of the converter was first introduced and the output gain when the energy flows in different directions was analyzed. Finally，on the premise of meeting the charge and discharge of the battery in the home distributed energy storage system，the devices and control parameters were designed to verify the correctness of the theoretical analysis.

Aiming at the problem of large output voltage fluctuation and long recovery time of three-phase pulse-width modulation （PWM）rectifiers when the load changes，an improved single-neuron gradient learning control strategy was proposed. Due to the poor adaptability of the traditional PI controller parameters when the load changes，a single neuron PI control was adopted in the voltage outer loop，and the gradient descent method was used to adjust the weight parameters online. In order to avoid falling into a local optimal solution during the solution process，a stochastic gradient descent algorithm with restart function （SGDR）was used，and cosine annealing was used to change the learning rate of the weights to improve the convergence performance of the algorithm. Through Matlab and hardware-in-the-loop simulation experiments，the dynamic response performance of the voltage outer loop of the three-phase PWM rectifier under different control algorithms was compared and analyzed. The results show that the three-phase PWM rectifier controlled by the improved single neuron PI algorithm has smaller voltage fluctuation，faster dynamic response and more stable operating state when the load changes.

In order to analyze the power quality problem of actual power network under the influence of uncertain interference factors，a power quality detection and recognition method combining empirical wavelet transform（EWT）and improved S-transform was proposed. On the one hand，the frequency，amplitude and time parameters of the AM-FM component were accurately extracted by using the EWT joint normalization direct orthogonal（NDQ）algorithm and singular value decomposition（SVD）algorithm. On the other hand，considering the instantaneous amplitude fluctuation of the EWT algorithm in the high noise environment，the improved S-transform was introduced to extract the time-frequency information of power quality disturbances under the high noise interference. Finally，based on the disturbance feature vectors extracted by EWT and improved S transform，the power quality disturbance recognition classifier optimized by the support vector machine（SVM）based on improved particle swarm optimization（IPSO）algorithm was used to accurately identify the disturbance types. Simulation and experiments show that the average recognition accuracy of the proposed method is 93.23% in the case of composite disturbance recognition and classification，and it can accurately identify four kinds of measured disturbance signals.

In the grid load control and planning of distribution network，in order to optimize the grid structure of distribution network，such as line loss，power supply quality and load，a grid load control and planning technology based on differential evolution algorithm was proposed. For all kinds of power generation devices in the distribution grid，the power grid planning model was established，the initial population was set and constructed，and the appropriate differential initial vector was selected for mutation processing. On the premise of forming a new individual under the difference increment，in order to improve the diversity of the population of future generations，the differential individual was cross trained by using cross factors to form a new distribution individual. Finally，the greedy selection model was used to evaluate and retain the offspring population，control the active power of controllable load and uncontrollable load，and complete the grid planning. The experimental results show that the load control and planning of distribution grid using differential evolution algorithm are better，the robust performance is superior，and the iteration speed is faster.

AC-DC hybrid power grid can balance the power flow during the operation of the power system in a large range，which is conducive to improving the access capacity and access range of large-scale access of new energy to the power grid，which is an important trend in the development of modern power grid. In order to analyze the structural vulnerability of AC-DC hybrid system and avoid the occurrence of power grid outage，a rank-sum ratio （RSR）method was proposed to analyze the structural vulnerability of power grid. Firstly，the vulnerability index set was established based on the structural characteristics of the complex networks. Secondly，the RSR method combined with the subjective and objective evaluation method was used to obtain the comprehensive weight value of node vulnerability. Finally，to verify the validity of the proposed method，AC-DC mixed with EPRI-36 node system node vulnerability analysis based on an example，the results show that the method is feasible.

Reasonable planning of the active distribution network is an important part to improve the wind energy accommodation capability，however，the overuse of the wind power output and load timing characteristics increase the difficulty of model solving and have adverse effects on the optimal results. The Latin hypercube sampling （LHS）combined with the K-means clustering was employed to reduce the number of samples，thus a typical wind power and load multi-scenario model with higher calculation efficiency can be obtained. Considering the interests of wind power operators and the State Grid Corporation，a bi-level planning model of active distribution network considering the wind power timing characteristics was established. The upper level determines the wind power planning scheme with the goal of maximizing benefit of wind power operators，and the lower level optimizes the system operation state with the minimum loss of distribution network. The effectiveness verification of the planning mode was conducted based on the IEEE 33-bus distribution system. The results show that the loss cost of the distribution system is 260 400￥after planning based on the GA-PSO joint optimization algorithm，which is 5.03% and 0.77% lower than that of single GA algorithm and PSO algorithm respectively，and the scenario cost is reduced by 40 000￥compared to that of the results calculated by GA algorithm and PSO algorithm. Therefore，the validity of the planning model proposed was verified.

In view of the fact that the original high-dimensional nonlinear power flow model cannot be applied to the linear planning of distribution network，and the existing linear power flow model has the problem of weak universality，a calculation method of distribution network linear power flow was proposed considering the static characteristics of load voltage and PV nodes. Based on the power flow equation in polar coordinates，the proposed method decoupled the voltage amplitude and phase angle of the power flow equation using the characteristics of the distribution network. According to the control characteristics of PV nodes，a linear power flow calculation model with PV nodes was derived. The proposed model not only considered the static characteristics of PV nodes and load voltages，but also considered the adaptability to overload and weak loop networks. It could solve the voltage distribution of distribution networks without iteration. The simulation results show that the proposed method has high accuracy and versatility，and can be used for rapid analysis of distribution networks.