In order to improve the stability and economy of photovoltaic-storage combined power station，a capacity optimization method of photovoltaic-storage system based on the whole life cycle was proposed. The basic model of the station was analyzed. The capacity optimization model of energy storage system was established based on whole life cycle theory. And the revenue and expenditure of the system were considered. The actual case was simulated and analyzed by the three schemes. It can be obtained that the optimal method of system capacity with the maximum net present value as the goal has high economy. The net present value is 809 thousand yuan and 738 thousand yuan higher than the method of taking power quality as the goal and not allocating energy storage，respectively. If the capacity of the energy storage system exceeds 3 MW，it will not give full play to the maximum benefit，it will lead to the saturation of system power sales revenue and assessment cost，then the battery loss cost is increased. The method of optimizing the system capacity by taking the maximum net present value as the goal can reduce assessment cost and battery loss cost，it can also increase the system power sales revenue and maximum net present value，and improve power quality.

In order to ensure the minimum carbon emission and optimal power distribution of the hybrid energy storage microgrid under the constraint of carbon footprint，a distributed coordinated control algorithm of the hybrid energy storage microgrid under the constraint of carbon footprint was proposed. Based on the whole life carbon footprint of mixed energy，the distributed coordinated control objective function of hybrid energy storage microgrid with minimum carbon emissions and optimal constant volume of mixed energy was constructed，and the constraint conditions were determined. On this basis，combining with the uncertain characteristics of hybrid energy storage microgrid，the objective function was rewritten to form a two-stage brodding optimization and coordination control model. Adopting column and constraint generation algorithm to solve the model，obtain the optimal solution of the objective function.The test results show that，after the application of this method，the carbon footprint coefficient is lower than 9.0，the power distribution result of ultracapacitor is about 4.8 MW，the maximum value of network loss power and maximum voltage deviation is 0.42 MW⋅h and 0.067 V respectively. The indirect and direct carbon emissions are significantly reduced，and the charged state of the hybrid energy storage system is effectively improved.

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.

Under the background of limited resources and time，equipment maintenance is considered as an effective way to maintain the stable operation of the system. In order to allocate maintenance resources efficiently，the most critical equipment in the system should be identified first namely those that will cause significant consequences if they fail. Firstly，a new multicriteria decision-making（MCDM） scheme was proposed to identify the critical lines in the distribution network. Different from the previous analytic based hierarchy process，the best-worst method （BWM） was adopted to obtain the weight of the system reliability index according to the knowledge and judgment of experts. In addition，the fuzzy theory was introduced into the traditional best-worst method to overcome the general uncertainty in expert judgment and decision making. Finally，the technique for order preference by similarity to an ideal solution technology was used to prioritize the maintenance of IEEE14 distribution network lines. The proposed method can determine the priority of system maintenance more quickly and accurately.

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.

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.

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.

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.

The state of the DC system of substation is directly related to the normal operation of the substation. A new method for ground fault detection in substation DC systems，which is a combination of double-tree complex wavelet transform and singular value decomposition，was proposed to achieve fast and accurate location of ground faults occurring in substation DC systems. Firstly，the method constructed a Hankel matrix to decompose the branch current signal through a dual-tree complex wavelet transform（DT-CWT）. Secondly，the Hankel matrix was decomposed by the singular value decomposition（SVD）method with the aim of obtaining a series of singular eigenvalues. Thirdly，the singular value difference spectrum was constructed using the adjacent singular value differences，and the number of singular values was retained by the maximum peak of the singular value difference spectrum. Finally，the low-frequency signal was reconstructed by the retained singular values. The analysis results of the algorithm show that the method can accurately extract the low-frequency AC signal from the branch current signal and achieve the accurate location of the DC system ground fault in the substation，which can largely reduce the influence of the ground capacitance on the detection accuracy.