The development status of electric drive systems in the industrial sector and their significance in promoting green and low-carbon transformation were studied. As a crucial control and energy-saving equipment in the industrial sector，electric drive systems face numerous challenges posed by unchecked development. It is imperative to enhance the overall quality and energy efficiency levels by optimizing the industry order. Firstly，the current development status of electric drive systems both domestically and internationally were analyzed，and discussed the energy efficiency requirements for products in the global community. Furthermore，problems encountered by electric drive products in the green and low-carbon development of China's industry were discussed. To promote sustainable development of electric drive systems，a green and low-carbon development path was proposed，including strengthening the standardization system for electric drive products，enhancing the implementation of standards，promoting mandatory certifications，and disseminating energy-saving technologies. Simultaneously，the importance of placing emphasis on and regulating the recycling phase of electric drive products was emphasized. Through these measures，electric drive systems hold promise to make a greater contribution towards the green and low-carbon transformation of industry.

The traditional control of electromechanical actuator in aviation electromechanical servo system mostly adopts two-level inverter and PID control，which can not achieve higher precision control of permanent magnet synchronous motor. In view of the above problems and the difficulty of space vector modulation algorithm to solve the problem of neutral point voltage balance，a model predictive control method based on improved virtual space vector method was proposed，and the corresponding control strategy was designed. The model predictive control was used to improve the control response speed and control accuracy of the permanent magnet synchronous motor. The neutral point clamped（NPC） three-level inverter with more sinusoidal output was used. The improved virtual space vector pulse width modulation（VSVPWM） was used to construct a dodecagon virtual space vector diagram closer to the vector circle. The simulation results show that the improved method can realize the stable operation of permanent magnet synchronous motor under low torque ripple，and has a good control effect on the midpoint voltage balance problem.

In response to the poor disturbance rejection performance and issues of parameter perturbation and control precision in traditional control strategies for interior permanent magnet synchronous motors （IPMSM），a fuzzy sliding mode control strategy based on the super-twisting disturbance observer was proposed. This strategy enables wide-speed-range operation of IPMSM，and further improves rotational speed tracking precision and the system's disturbance rejection capabilities. Firstly，the speed control range was broadened by combining maximum torque per ampere ratio with the gradient descent method for weak magnetic control. Secondly，the super-twisting algorithm（STA）was utilized to design a disturbance observer，thus enhancing the system's ability to resist disturbances. In addition，to address the derivative explosion problem in Backstepping control，a second-order sliding mode differentiator was used to approximate the virtual control rate. The fuzzy logic system was adopted to approximate the nonlinear part in the model of IPMSM，reducing the impact of motor parameter perturbation on control performance. Finally，the stability of the proposed control strategy was confirmed by applying Lyapunov theory. Through simulation on the Matlab/Simulink platform，it was verified that under the control strategy proposed，IPMSM demonstrate superior wide-speed-range dynamic performance and robustness.

Aiming at the problem of insufficient frequency modulation capability of direct-driven wind turbine under traditional virtual inertia control，a control strategy of super capacitor assists direct-driven wind turbine participating in frequency modulation was proposed to improve the frequency stability of power grid after wind power is connected. Firstly，the influence of the fan speed and output power on the frequency modulation capability when the direct-driven wind turbine participates in the frequency modulation through virtual inertia control is analyzed，and the frequency modulation coefficient was established through the Sigmoid function to characterize the frequency modulation capability of it under different operating conditions. Then，based on the frequency modulation coefficient，a frequency modulation strategy for wind storage was proposed，that is when the frequency modulation ability of direct-driven wind turbine is strong，the direct-driven wind turbine participates in the frequency modulation independently，while when the frequency modulation capability is weak，the power required for the frequency modulation is jointly provided by the direct-driven wind turbine and the super capacitor. At the same time，the charging and discharging coefficient was introduced into the power control of the super capacitor to avoid its over-charging and over-discharging. At last，the simulation results show that the proposed method is better than the traditional virtual inertia control when frequency modulation capability of the direct-driven wind turbine is insufficient，and it also avoids overcharging and discharging of super capacitor.

When the Vienna rectifier is connected to unbalanced loads operating under light load conditions，the slight power difference causes unbalanced voltage of bipolar DC bus，which increases the voltage stress on the switching device and DC-link capacitance. To solve the above problems，a DC offset reduction of neutral point voltage strategy based on reactive current compensation for Vienna rectifier with bipolar DC-link was proposed. By combining the amplitude of zero-sequence component，which is superimposed onto the three-phase reference voltage，the neutral point current for various power conditions can be obtained. The effect of the phase angle difference between the reference voltage and the input current on the neutral point current was analyzed，and the maximum reactive currents of the odd and even sectors was obtained according to the operating region of the Vienna rectifier. In order to increase the neutral point current under light load condition，the reactive current was injected to change the phase angle difference according to the contour of neutral point current，thereby achieving the balance of bipolar DC bus under light load conditions. Finally，the effectiveness of the proposed strategy was verified on the Vienna rectifier experimental platform.

Switching power supply is now developing towards high-frequency soft-switching and high power density，the volume of magnetic components is greatly reduced，and the excitation inductance of transformer no longer meets the assumption of large excitation inductance in traditional analysis. Under this background，the influence of the weak excitation inductance on the full-bridge circuit was analyzed，and proposed that the full-bridge circuit can achieve autonomous soft-switching through the charging and discharging of the capacitor under the condition of the weak excitation inductance. The autonomous soft-switching of the full-bridge converter can be realized when the duty ratio is large. Through principle analysis and calculation，relationship between the charge and discharge of the switch body capacitance and the inductance current and the time constant was obtained，and the above principle through simulation were verified. Finally，an experimental platform with a working frequency of 200 kHz was built to verify the above analysis and simulation results.

In order to solve the problem of large peak-to-peak inductor currents in dual active bridge converters with mismatched input and output voltages，a four-degree-of-freedom modulation（FDFM） strategy was proposed by combining symmetric duty cycle modulation and asymmetric duty cycle modulation. By analyzing the operating modes of the four-degree-of-freedom modulation strategy，the peak-to-peak inductor current and transmission power models were established，and the optimal solution with different transmission powers was solved by using the Karush-Kuhn-Tucker（KKT） condition with the peak-to-peak inductor current as the optimization objective. And the experimental prototype was built to verify the effectiveness of the proposed strategy. The experimental results show that the proposed modulation strategy can effectively reduce the peak-to-peak inductor current of the converter and improve the efficiency of the dual active bridge converter.

With the continuous increase in the scale of distribution network construction and operation，a large number of electricity load control problems have emerged，especially the weakening of sample time series characteristics in electricity load data analysis，resulting in incomplete acquisition of local load characteristics，making it impossible for the distribution network electricity load prediction system to maintain the balance of energy in the power grid. In the past，the impact of "source-load" uncertainty was also rarely considered in the distribution network electricity load processing and distribution，which can easily lead to low probability of electricity load classification recognition，significant errors in electricity load prediction，and long-term problems such as high generation costs and insufficient distribution balance. In response to the above situation，the uncertainty of "source" and "load" was conducted research through probability distribution functions. A multi-objective function composed of two probability distribution functions was set as the constraint conditions for the coordinated output balance. The improved cluster eddy current search algorithm was used to solve the problem，and a coordinated control scheme for electricity load was obtained. The test results show that at 17：00，the power of photovoltaic device 1 is 1 050 kW， at 11：00，the power of photovoltaic device 2 is 980 kW，based on the source-load uncertainty root-mean-square error of less than 0.7%. The cost of the scheme based on "source-load" uncertainty is 453 200 yuan，and the balance degree is 0.94. The collaborative control method based on "source-load" uncertainty has a higher balance than the collaborative control method without "source-load" uncertainty，and the collaborative control technology is more reasonable.

In response to the potential frequency secondary drop problem of direct-drive wind power systems in the scenario of continuous frequency drop faults in the power grid，the principle of primary frequency regulation of direct-drive wind power systems was analyzed. A primary frequency regulation control strategy for direct-drive wind power systems was proposed based on the product and difference combination of frequency change rates at pre- and post-sampling times. According to the established criteria，the droop coefficient of the direct-drive wind power system in different frequency response stages was adjusted by comprehensively considering the fan speed，frequency deviation，and frequency rate of convergence，to realize the active frequency support and flexible frequency modulation exit of the wind power system. A simulation model of a direct-drive wind power system was established in Matlab/Simulink to verify the effectiveness of the proposed control strategy.

The micro-grid solves the problem that the intermittent and fluctuating power generation has adverse effects on the stable operation of the distribution network when the distributed generation is connected to the distribution network. In order to meet the economic operation of micro-grid under grid connected mode and improve power supply reliability，a micro-grid energy dispatching strategy based on peak-valley price and energy storage state of charge （SOC） was proposed. The strategy divided the whole day into three periods：peak，average and valley. During the real-time scheduling cycle，different scheduling strategies were applied based on different time interval and the SOC of energy storage. Reasonable energy storage charging and discharging penalty functions were designed in different time interval，and the maximum energy storage charging and discharging constraint factor was introduced to further improve the charging and discharging of the energy storage device. The minimum operating cost of micro-grid was took as the objective function and solved it through particle swarm optimization algorithm. The effectiveness of the strategy was verified by an example analysis.

In order to improve the accuracy and stability of short-term wind direction prediction，a wind direction prediction method based on lidar wind data and an improved nonlinear echo state network （NESN） model was proposed.First of all，wind direction data 100 meters ahead of the wind turbine was obtained by laser wind detection radar. Secondly，the multivariate polynomial function was used to construct the nonlinear relation of the internal state of the reserve pool，the order of the weight matrix and the complexity of model calculation were reduced.Finally，the prediction model was established and the simulation prediction was carried out on different lidar data sets.The results show that compared with the nonlinear echo state network and adaptive neuro fuzzy inference system （ANFIS），the mean absolute error （MAE），root mean square error （RMSE），normalized mean absolute error （NMAE）and normalized root mean square error （NRMSE）of the improved NESN model are significantly reduced，and the prediction accuracy and stability are improved.The accuracy of the wind turbine alignment the wind direction is improved and the mechanical loss of yaw is reduced.

Over the years，machine learning has made some breakthroughs in the insulation defects of gas insulated switchgear（GIS），but the traditional methods have the disadvantages of incomplete information，excessive reliance on artificial feature extraction and low diagnosis rate. In order to solve these problems，a diagnosis method based on deep graph convolutional neural network （DGCN）was proposed. Firstly，a partial discharge （PD） experimental platform was built on a 220 kV real GIS and the partial discharge signals collected by ultra high frequency sensor were converted into frequency domain spectrogram samples by Fourier transform. Then，the spectrogram samples were input into the DGCN，which undergoes graph convolution，coarsening and pooling operations to make the spectrogram structure was clearer and enrich the input information. Finally，the test samples were used to test the DGCN with set parameters. The experimental results show that the proposed method can achieve a recognition rate of 98.77% for GIS fault defects，which is significantly higher than other methods and has good robustness.