The traditional three-loop position control applied in the servo system with elasticity causes residual vibration around the objected position and has long trailing time. To address this issue，a mathematical model of the two-inertia system was established，and the causes of low-damping of the traditional position closed-loop structure were analyzed in detail. It was proposed to modify the speed loop structure combined with resonance-ratio control to guarantee the high-damping of the closed-loop system. The controller parameters were designed by use of the equal real part design，zero-pole elimination and polynomial method to achieve the high-damping characteristics. Simulation results show that the proposed high-damping position control can well suppress the fluctuation，achieve smooth position tracking，significantly reduce the trailing phenomenon compared with traditional P-PI method.

The synchronization accuracy of a multi-motor speed synchronization system is influenced by the motor control algorithm and synchronization control strategy. In response to the shortcomings of existing control strategies，a mid-range deviation coupling control strategy for multi-motor speed synchronization systems was proposed. Firstly，a mathematical model of multi permanent magnet synchronous motor was established. On the basis of the deviation coupling control strategy，the motor speed deviation was calculated using mid-range speed，and the structure of the deviation coupling control was optimized. The controller was designed using a nonsingular Terminal sliding mode control algorithm. Then，the Lyapunov stability theory was used to analyze the stability of the designed controller. Finally，a multi-motor synchronous control test platform was established for test verification，and the test data was analyzed. The results show that the proposed control strategy is effective and can improve the synchronization performance of the system.

In order to alleviate the intensive computational burden in the model predictive control（MPC）of the matrix converter，the MPC of the matrix converter was divided into the predictive control of the virtual rectifier and virtual inverter based on the equivalent indirect modulation of the matrix converter. Compared with the traditional direct MPC，the computational burden and execution time of the proposed strategy were reduced. Considering the issue of the high dependence of MPC on model parameters，the extended Kalman filter（EKF）was used to identify system model parameters online，thereby improving the robustness and anti-interference ability of MPC. The experimental results show that the proposed indirect MPC based on the extended Kalman filter parameter identification algorithm offers a good control performance on the load current and the grid side power factor control，and the dependence on the model parameters is reduced.

Accurately estimating the state of health（SOH）of lithium-ion batteries is a crucial prerequisite for ensuring the safe and stable operation of energy storage systems. The key to improving the accuracy of SOH estimation lies in the rational selection of health characteristics that can effectively reflect the state of health of lithium-ion batteries. By analyzing the current characteristics of lithium-ion batteries during the constant voltage charging stage，a healthy combination of features containing the slope of the first and last points of the current curve，the standard deviation，and the mean value were extracted from the current curve data during the constant voltage charging stage. To validate the effectiveness of the proposed feature combination，SOH estimation model based on kernel ridge regression（KRR）and support vector regression（SVR）was designed，and model validation was successfully completed. The experimental results demonstrate that the proposed feature combination can achieve high-precision SOH estimation across different models，exhibiting excellent model adaptability.

Aiming at the problems of insufficient stability and low power generation efficiency of the existing power supply means for offshore ocean observation equipment，and low power density of direct drive wave energy power generation device due to the low running speed of ocean waves，it proposed to apply the magnetic lead screw（MLS） as a speed increasing device in the field of wave energy power generation，and based on its topology，the magnetic vector potential energy theory was introduced to establish a two-dimensional magnetic field analytical model，and the speed increasing operation mechanism of the magnetic lead screw was expounded. On this basis，the structure of surface-mounted magnetic lead screw was optimized and its thrust and torque performance was analyzed. Meanwhile，a magnetic lead screw composite generator was designed according to the optimization results，and the output power was compared with that of a cylindrical external permanent magnet linear generator under different wave speeds and load conditions. The simulation results show that the output power of the magnetic lead screw composite generator under the same volume was greatly improved compared with that of the cylindrical external permanent magnet linear generator in the low-speed wave motion condition，which is more suitable for the low-speed and large-thrust direct drive wave energy power generation field.

In order to improve the power coordination ability among microgrids in the microgrid group，it is necessary to consider the correlation between renewable energy generation output and the difference in load time distribution in different regions in the microgrid group planning. A scenario generation method that considers the spatio-temporal correlation of renewable energy power generation was proposed. Based on the spatial distance between microgrids in microgrids and the temporal characteristics of renewable energy power generation output，Nataf transformation and temporal reconstruction methods were used to generate scene-solar power output scenes that meet the temporal and spatial correlation. Then，the capacity allocation model of multi-objective microgrid group with minimum annual total cost and cumulative source-load difference was established. Finally，Jaya algorithm with non-dominated sorting and congestion improvement was adopted to solve the problem. Fuzzy membership function was used to evaluate the Pareto solution and select the optimal allocation scheme of wind storage in microgrid group. The results of the example show that the total investment cost can be effectively reduced by the precise allocation of the source storage capacity of the microgrid cluster，while the carbon emission level of the microgrid cluster can be reduced and the absorption capacity of renewable energy can be improved.

New energy has obvious volatility and anti-peak-shaving characteristics，and the integration of large-scale new energy into the power grid poses challenges to the peak-shaving. Hydrogen energy has a good potential for application as a potential peak-shaving resource. A multi-time scale peak-shaving scheduling model based on electrolytic hydrogen production was proposed with the aim of solving this problem. Firstly，the evaluation index model of peak-shaving capacity of electrolytic hydrogen was introduced and different types of electrolytic hydrogen peaking capacity were caculated. Meanwhile，an equivalent load disaggregation model based on coordinate distance minimization and wavelet transform techniques was constructed for matching different equivalent load components with different electrolytic hydrogen production systems. Subsequently，a multi-time scale peak-shaving scheduling scheme for different load components was proposed with the objective of improving the economics and effectiveness of peak-shaving. Finally，the validity of the proposed model was confirmed through simulations on the IEEE-30 node system.

The proportion of new energy sources connected to the station area is increasing day by day，which inevitably brings regulatory needs. Therefore，there is an urgent need for corresponding edge power flow algorithms. In order to give consideration to accuracy，practicality and efficiency under the situation of weak communication conditions and limited computing resources，a real-valued power flow algorithm for the edge computing of 400 V station area was proposed. Considering the resistive nature of the 400 V station area network and the high power factor of the equipment，the AC variables were simplified from vector sum to scalar sum；corresponding node transformation strategies and iterative algorithms were designed ；assignment strategies in the case of missing data was proposed；an online calculation strategy based on sensitivity correction or iterative calculation was further proposed. Through simulation analysis，the accuracy and practicality of the algorithm proposed were finally verified.

The massive access of 5G base stations has injected new vitality into the low-carbon development of integrated energy system （IES）. By stimulating 5G base stations to participate in demand response and incorporating them into the scheduling framework of IES，energy saving and emission reduction of IES can be effectively promoted and the overall economic benefits of IES can be improved. Accordingly，a campus IES day-ahead scheduling model that considers low-carbon empowerment of 5G base stations was proposed. Firstly，the basic structure and main energy consumption inside the 5G base station were analyzed，and a flexible interaction model between the 5G base station and the IES system was constructed；secondly，a price-based demand response model based on the price elasticity matrix and a substitution-based demand response model based on the electric energy-thermal energy interconversion were constructed，and the IES day-ahead scheduling model was built with the lowest scheduling cost as the objective function；meanwhile，the IES risk-averse robust model was further constructed by using the information gap decision theory to deal with the uncertainty of renewable energy output. Finally，the effectiveness of the proposed model and the proposed algorithm were verified by various typical operation scenarios in an IES system.

The participation of wind power and energy storage in primary frequency regulation of power grid can make better use of the advantages of wind power and energy storage for frequency regulation，which has gradually become a new trend. However，there are some problems in the coordination of wind power system and energy storage，such as insufficient utilization of energy storage and mismatch of wind power and energy storage power. Aiming at the above problems，an improved wind-storage combined primary frequency control strategy was proposed. Through frequency separation，design of six operating conditions and the switching rules，optimization of wind power and energy storage adaptive droop coefficient，the charging and discharging function of energy storage battery was realized，the power mismatch problem in operating condition switching was improved，and the excessive compensation of power shortage caused by this was avoided. Finally，the wind energy utilization efficiency and frequency regulation effect of the proposed control strategy and the existing control strategy were compared through simulation and wind storage experimental platform，and the effectiveness and superiority of the proposed control strategy were verified.

Static var generator（SVG）can governance power quality，energy conservation and reduce consumption，furthermore it is an energy consumption product.The reasonable evaluation of the energy saving of the device has become an urgent problem to be solved. The power saving measurement technology of products was studied，and it was found that the existing power saving verification methods are not test methods. Because the field conditions are not unified，the verification results are not comparable. They can not be the data support of energy saving evaluation. At present，there is no set of effective testing methods in the field of inspection and testing that can be used for the power saving measurement of products in third-party testing laboratories，which makes both the testing work and energy saving evaluation work cannot be carried out.In order to make up for the above proposed detection technology gap，the innovative test method of design simulation resistance was proposed，so as to help complete the power saving measurement work. And a test platform was set up in the laboratory，to verify the feasibility and correctness of the method，and to assess the dispersion of the measurement results.The final conclusion is that the proposed method can be used for the third-party laboratory to complete the power saving measurement，flexible and controllable test conditions，can meet the requirements of various working conditions of the manufacturer，and the measurement results are comparable，can become the data support of energy saving evaluation，promote product iteration and update，and promote the progress of the industry.