With the continuous development of renewable energy sources and the increasing share of renewable energy in the grid，optimal coordination of maintenance work becomes increasingly important in order to ensure the safety of power supply in power systems considering renewable energy access. Current tools for maintenance planning are constrained by operational safety standards and the complexity of the grid，and have problems such as low operability and high computational effort to simulate accidents. To reduce the burden of manual computation，the use of machine learning models was proposed to predict the outcome of emergency situations in a fast and reliable manner. The method was tested in a regional facility in Lanzhou，covering voltage levels of 10 kV and 220 kV. By testing and comparing a plain Bayesian classifier，a support vector machine （SVM）and a decision tree-based model，it was shown that the decision tree-based random forest algorithm is consistently better than other algorithms in identifying safe serviceable time periods with an accuracy rate higher than 90%. In addition，it was shown experimentally that the expected growth in renewable energy generation will affect the future serviceability of the power system，with a 20% increase in non-safe serviceable time periods in some areas.

As the penetration rate of new energy and power electronic equipment increases，the inertia and damping of the power system decrease，and the stability decreases.The grid-forming control technology builds a voltage source to support the stable operation of the large power grid through the converter，so as to play the role of rapid frequency and voltage regulation，increase inertia and short-circuit capacity support，and suppress broadband oscillation，so it has gradually attracted attention. Firstly，the differences between the grid-following converter and the grid-forming converter were compared，and the grid-forming control technology was more suitable for the new power system. Secondly，according to the four different control strategies of the grid-forming converter，the control mechanism of these strategies was analyzed in principle.Finally，by using the same initial parameters and simulating the influence of different control strategies on the power grid frequency after the power grid was disturbed by common disturbances，the superiority of VSG control strategy was verified，and the influence of VSG virtual moment of inertia and damping coefficient on the output frequency response of the system was discussed，which provides a reference for further in-depth research.

A sliding mode linear self disturbance rejection control strategy was proposed to address the output voltage fluctuations caused by sudden load changes，changes in DC bus voltage，disturbance addition，and other disturbances in three-phase interleaved parallel DC-DC converters. Firstly，a mathematical model of three-phase interleaved parallel DC-DC converter in the s domain was established and the principle of energy transmission imbalance was analyzed. Then，based on the system order，appropriate observers and linear auto-disturbance rejection controllers were designed. Furthermore，in order to improve the ability to suppress the fluctuation of the output voltage of the system，sliding mode control was introduced to form a sliding mode linear auto disturbance rejection control，which improves the anti-interference and rapidity of the system.Finally，multiple operating conditions were designed to simulate and verify the new control strategy. The results show that compared with traditional control strategies，sliding mode linear active disturbance rejection control not only has excellent voltage fluctuation suppression ability，but also has superior steady-state operation ability and transient traversal ability，ensuring the balance between system capability transmission.

In the context of dual carbon，carbon trading mechanism and various energy complementary power generation mechanism are important mechanisms for China to achieve carbon emission reduction goals and sustainable development. A multi-energy system optimization model was proposed that takes into account carbon trading to reduce carbon dioxide emissions while relieving the pressure of thermal power unit peaking. Firstly，a cost model of carbon trading was constructed based on carbon emissions，taking into account coal consumption cost，fuel input and loss cost and environmental cost，to form an optimal objective function and linearize it by segments. Secondly，the model for hydro-thermal-wind-photovoltaic power system was constructed. In the first stage，with the objective of minimizing net load fluctuation，the generation capacity of each hydropower station of the terrace was calculated using the moth search （MS） algorithm，and the daily load output curve was optimized. In the second stage，with the objective of minimizing the integrated cost and describing the stochasticity of wind power with the help of scenario method，a dispatching model of power system considering carbon trading mechanism was constructed. Finally，the validity of the proposed model was verified in a modified IEEE 7-machine 57-bus system.

The power cable plays a very important role in today's social development and urban operation. With the increase of people's electricity consumption，the amount of cable laying is also increasing synchronously.In order to prevent the cable from being damaged，the environmental vibration signals around the cable duct gallery are monitored，and potential threats are found in time to ensure the normal operation of the cable，a vibration monitoring system for underground cable damage prevention based on Matlab wavelet noise reduction algorithm and EMD-AR spectrum analysis was proposed. The system was composed of solar power supply module，six axis gyroscope attitude sensing module，vibration sensor module and internet of things communication module.The main control chip uses STM32F4 microcontroller. The wavelet threshold de-noising algorithm was used to remove the complex high-frequency noise and improve the signal identifiability. Then the de-noised signal was subjected to empirical mode decomposition（EMD）and AR spectrum analysis of the first six intrinsic mode function（IMF）components.Finally，the AR spectrum of the first six IMF components was accumulated to obtain the energy contrast map of the signal. The research shows that the application of this method can accurately analyze the type of vibration，which can provide a more simple and convenient method for the monitoring and analysis of vibration near the cable duct gallery，and effectively protect the safe and stable operation of the cable.

The integration of large-scale wind power，photovoltaic and other renewable energy resources for the power system will greatly change the power supply characteristics，reducing the inertia of power system and threatening the stability of transient frequency. The virtual synchronous generator（VSG） technology can improve the inertia of renewable energy to promote the stability of transient frequency. In order to quantitatively describe the characteristics of transient frequency of VSG and enhance the control ability of VSG，the transient frequency model of VSG needs to be studied urgently. Based on the VSG control strategy of renewable energy，considering the inertial response，primary frequency regulation of renewable energy，the transient frequency model of VSG was established，and a Matlab/Simulink based simulation model was built to verify the validity of the established analytical model. Finally，the influence of different control parameters on the transient frequency of VSG was analyzed，and the effect of control parameters on the transient frequency of VSG was clarified，giving the guidance for system frequency stabilization.

Because of crystal oscillator error，inter-symbol interference and baseline drift in industrial optical fiber communication，the optical fiber receiver has the problem of high error rate of data recovery. In long-distance industrial communication，the electrical level jitter of serial data at the receiver will increase. To solve this problem，a method of clock and data recovery for long-distance industrial optical fiber communication was proposed. Six-times frequency clock was used for sampling. The rising or falling edge of serial data can be determined and collected under the same clock，which can select dynamical sampling clock. According to the electrical level jitter tolerance，the validity of the sampled data under different conditions can be verified. After data processing，the six-times sampled data was restored to serial data under the local clock，which is finally converted to the parallel data. Simulation and test verified the effectiveness of the proposed method.

With the proposal of the "dual carbon" goal，the application of EVs is becoming increasingly widespread. In order to further reduce the charging cost of EVs so as to easing the charging cost burden of EV users，a coordinated control strategy for EV charging DC microgrid was proposed，which includes photovoltaic（PV），energy storage system（ESS）and power grid. This strategy can coordinate the input and output states of different ports based on the power relationship between each port，reduce the fluctuation of EV charging load through peak shaving and valley filling thus lowering the charging cost. Firstly，the control strategies of PV and ESS were introduced. Then，Monte Carlo algorithm was used to predict the charging load of EVs. Next，six modes and four voltage bands during microgrid operating was divided，mode switching condition and coordinated control strategies between each port were proposed. Subsequently，the feasibility of coordinated control was verified in Matlab/Simulink and Yuankuan semi-physical simulation platform. Finally，by calculating EV charging costs under five typical weather scenarios and comparing them with other literature，it was found that the proposed strategy can reduce charging costs by up to 28.1%，its significant effect in reducing costs was demonstrated.

A method for establishing edge triggered pulse control switch state time was proposed to address the divergence of floating capacitor voltage and DC capacitor midpoint voltage in a 5-level active neutral point clamped（ANPC-5L）inverter using the space vector pulse width（SVPWM）algorithm in the g-h coordinate system. The fluctuation of floating capacitor voltage and the offset of DC side capacitor voltage were reduced. The principle that the fluctuation of the floating capacitor current causes the voltage deviation of the floating capacitor was used. Based on the principle that the same level is output under different switch states，and different switch states cause the current direction of the floating capacitor to be opposite，within a complete cycle，the floating capacitor current cancels out each other，reducing the voltage fluctuation of the floating capacitor. An active power flow model was established to balance the midpoint voltage of the DC side capacitor by reducing the voltage fluctuation of the floating capacitor. Finally，by building a simulation platform and comparing the capacitor voltage balance of ANPC-5L before and after the application of the proposed method，the validity of the method was verified.

The multi-source monitoring data of switchgear contains rich equipment operating status information，and analyzing it can achieve switchgear fault diagnosis. A fault diagnosis method for switchgear based on SMOTE-SSA-CNN was proposed. Firstly，based on monitoring data such as switchgear voltage，current，and temperature and humidity，the synthetic minority over-sampling technique（SMOTE） algorithm was used to expand the original dataset，solving the problem of severe imbalance between positive and negative samples in the original dataset. Then，the sparrow search algorithm（SSA） was introduced to optimize the hyperparameters of convolutional neural networks（CNN），such as the size and number of convolutional kernels，the number of fully connected layer neurons，and the learning rate，in order to improve the accuracy of the model's fault diagnosis results. Finally，the performance of the established SMOTE-SSA-CNN model was evaluated through example analysis，verifying the effectiveness of the proposed method for switchgear fault diagnosis. Compared with traditional fault diagnosis methods，the proposed method has better convergence and higher accuracy.