Aiming at the problem of power quality deterioration caused by a large number of high-permeability distributed generation connected to the distribution network，a power quality assessment method based on combination weights and vlsekriterijumska optimizacija i kompromisno resenje（VIKOR） method was proposed.Firstly，according to the existing standards and the actual engineering situation，a comprehensive evaluation system of power quality was established from three dimensions：amplitude quality，waveform quality and frequency quality.Secondly，considering the defects of the traditional nine-demarcation analytic hierarchy process（AHP）method，the three-demarcation was used to improve the AHP method to obtain the subjective weight. In order to avoid the shortcomings of the single weighting method，the objective weight was obtained by combining the entropy value in the entropy weight method with the amount of information in the criteria importance though intercrieria correlation（CRITIC）method. This method considered the degree of dispersion，correlation and contrast between the indicators，and the subjective and objective weights were combined by the Lagrange multiplier method. Then，the VIKOR method was used to obtain the comprehensive evaluation value of each power quality index and sort its merits and demerits. Finally，the power quality index data collected by five monitoring points in a certain area were used for case analysis and compared with other evaluation methods to verify the feasibility of the proposed method.

Among the junction temperature monitoring methods of insulated gate bipolar transistor （IGBT），the temperature-sensitive parameter method has attracted wide attention because of its fast response speed，low cost and easy on-line detection. Previous studies have shown that the gate threshold voltage （ V_{TH}）among the temperature-sensitive parameters has good temperature properties，but it is easily affected by current oscillation by direct measure-ment. Therefore，an indirect calculation method of threshold voltage based on Miller platform under resistive load was proposed. Firstly，the switching transient process of IGBT under resistive load was described，and the theoretical basis of V_{TH} indirect calculation method was discussed. Then，the V_{TH} was calculated indirectly by the voltage value of Miller platform in the switching process. Finally，the effectiveness of the method was proved by experiments.

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.

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.

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.

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.

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.

In order to improve the debugging and fault monitoring and analysis capabilities of inverter products，the design scheme of network version process data acquisition and analysis software was proposed.The composition and implementation of the software system were discussed，and the technical means such as multi-thread，virtual memory，drawing class library and high-speed fiber synchronization were proposed to solve the technical problems of system operation. The field application of this software system shows that the system runs stably，has the characteristics of low cost，multi-channel transmission，low sampling period，high data accuracy，rich graphics functions，and strong scalability.

With the accelerated construction of new power system，the harmonic characteristics of power grid are becoming more and more complex. It is of great significance to study the effective statistical management of harmonic data for evaluating the power quality of power grid. A statistical method of harmonic evaluation index based on maximum entropy principle was proposed. By recording and saving the average value and center distance of harmonic data，the maximum entropy principle was used to fit the probability distribution of harmonics，so as to save and identify the harmonic characteristics and facilitate data storage. Two harmonic evaluation criteria of harmonic 95% probability value and 99% probability value were obtained by using the fitted probability distribution，which ensures the accuracy and consistency of the index. Finally，the effectiveness of the proposed method was verified by the example analysis of harmonic measured data.