As the penetration rate of household distributed PV in China's low-voltage distribution network continues to increase，the power flow of the distribution network has changed，leading to more serious problems such as node voltage overruns and three-phase imbalance，which poses a serious threat to the safe and stable operation of the distribution network. For situations where the distribution network topology and line parameters are unknown，the traditional voltage control strategy based on power flow calculation is no longer applicable， a data-driven voltage coordination control strategy was proposed for low-voltage distribution networks with high household photovoltaics penetration. First，a linear approximation model of the low-voltage distribution network was established，and the least squares method was applied to fit the relationship between node power and voltage based on the historical operation data of the low-voltage distribution network. Then，the photovoltaic inverter and energy storage system were used as regulation measures to minimize the degree of node voltage over-limit，minimize the three-phase unbalance and minimize the amount of equipment regulation as the objective function. The improved multi-objective particle swarm algorithm was utilized to achieve voltage optimization control. Finally，the effectiveness of the proposed voltage coordination control strategy was verified by simulation comparison and analysis with other control strategies and methods，taking the 21-node low-voltage station as an example.

Voltage source converter （VSC） is prone to low-frequency oscillations of 10⁰~10¹ Hz when connected to weak AC power grids. The mechanism of improving the control strategy of VSC on the traditional inverter side to suppress low-frequency oscillations（LFO） in the AC power grid is to transfer the oscillations from the AC side to the DC side，which poses a risk of inducing instability in the DC system. An adaptive voltage power damping control strategy was designed that can suppress low-frequency oscillations in AC systems based on the adjustable output power of the interface converter of energy storage devices containing new energy storage stations. This strategy was based on a damping control loop embedded in the rectifier side VSC control system，which suppresses DC voltage oscillation by controlling the output power of the rectifier energy storage system，effectively solving the shortcomings of traditional inverter side VSC control strategies in transferring oscillations. Based on the analysis of small signal stability，the parameter design process of the virtual damping control link was provided. The simulation results in Matlab/Simulink environment verified the effectiveness of the proposed control strategy and the correctness of the parameter design process.

The islanding detection method is a necessary method for grid-connected PV systems，but，the current islanding detection method is prone to misjudgement when encountering grid operation states such as high-resistance short-circuit ground faults and large-capacity load casting. For this reason，an islanding detection method based on reactive power perturbation and featured kurtosis was proposed based on analyzing the difference between the power at the grid point in the islanding operation state and other grid operation states. The method firstly used the three-phase voltage amplitude offset rate at the grid point to realize the starting criterion of active reactive power injection in PV system. Then，the apparent power waveform at the grid point was obtained，and after the normalization operation was performed to obtain the normalized apparent power （NAP） waveform，variational modal decomposition algorithm was used to decompose NAP at 8 layers，and the time-frequency component at layer 5 was obtained as the feature detection component. And then the feature detection component was characterized by a featured kurtosis to achieve islanding detection. Finally，a typical PV grid-connected system was constructed using Matlab simulation platform，and the effectiveness of the proposed method was tested through the working conditions of islanding operation with different quality factor loads，different high-resistance short-circuit ground faults，large-capacity load switching，and lightning strike faults，and so on.

To address the complexities of transformer condition assessment indicators and the overreliance on expert judgment in the evaluation process，a novel method for fuzzy comprehensive assessment of transformer condition was introduced，which is based on gaming theory and an improved version of the D-S evidence theory. First，the analytic hierarchy process （AHP） and the Critic method was adopted to determine both the subjective and objective weights of the evaluation indicators. These weights are then combined using game theory，reducing the dependence on expert opinions in traditional weight determination methods. Second，instead of traditional membership functions，cloud models was employed to preserve the inherent uncertainty in fuzzy assessments. Finally，membership information at the project level was fused by using improved D-S evidence，eliminating paradoxical results that can occur when combining high-conflict evidence. Through the results of case studies，the method effectively assesses the transition probabilities of various transformer states.

With the wide application of solar photovoltaic panels，the detection of hidden dangers and faults of photovoltaic panels has become more and more important. In order to improve the inspection efficiency of photovoltaic panels and the accuracy of defect detection，a target detection algorithm based on attention mechanism was designed and a complete inspection scheme of photovoltaic panels combined with UAV technology was proposed. The method uses the high-resolution camera mounted on the UAV for image acquisition，and detects and identifies the defects of photovoltaic panels through the combination of the object detection of the attention mechanism and the UAV technology. The experimental results show that the proposed method has high accuracy and reliability in photovoltaic panel inspection，mean average accuracy （mAP） reaches 83.2%，F1 score is 84.5%，effectively improve the quality and effect of photovoltaic panel inspection，and has high practical value.

Focusing on the central position of AC power frequency converter in the development of the national economy，emphasizingd their critical impact on the safety and efficiency of industrial production. In view of the rapid development of power electronics technology，the field of AC power frequency converter has made remarkable progress，but also faces many challenges，such as uneven product quality，and there is an urgent need to optimize the industry order to improve the overall quality level. By comparing and analyzing the development status quo of power supply systems at home and abroad，the high standard of product reliability required by the international community was revealed，and provided an in-depth analysis of the problems that exist in China's AC power frequency converter products in terms of reliability，standardization and regulation. In order to promote the high-quality development of the industry，a series of strategies were put forward：strengthening product reliability technology research and development，building a standardized evaluation system，ensuring the effective implementation of standards，promoting the power supply product certification system，and strengthening the operation and maintenance regulatory mechanism. These comprehensive measures are aimed at optimizing the industry ecosystem，improving product quality and safety，and thus promoting the high-quality，sustainable development of the AC power frequency converter industry.

Aiming at the problem that the circulating currents analysis of modular multilevel matrix converter（M3C） is not deep enough and the frequency component of circulating currents is not clear，the coupling process of submodule capacitor voltage fluctuation，bridge voltage fluctuation and circulating currents in M3C was deeply analyzed，and the primary coupling model of M3C circulating currents and its four main frequency components were obtained. The analysis results provided a theoretical foundation for using PR controller to suppress the circulating currents of corresponding frequency components. The theoretical analysis and suppression of circulating currents were verified by experiments. The experimental results prove that the theoretical analysis of the frequency components of circulating currents is correct，and it is also proved that the PR controller designed according to the analysis results has better suppression effect on circulating currents than the P controller.

As the penetration rate of new energy in the power system continues to increase，the large-scale grid connection of wind power is one of the important factors affecting the stable frequency operation of the power system. Configuring energy storage can provide transient frequency support for the system，improve wind power fluctuations，and enhance the stability of wind power generation. Firstly，by considering the primary frequency regulation requirements of wind farms and starting from the operating status of batteries，a state of charge （SOC）control strategy taking into account charge coefficient and discharge states was proposed，and a battery service life model was established. On this basis，with the overall goal of minimum sum of annual comprehensive costs of wind storage systems，a power and capacity optimization configuration model for energy storage systems was constructed that taken into account the state of charge and battery life. Secondly，the ant lion algorithm was used to solve the optimization results，and the effect of complex cost，battery life，and charge status on the optimization result was analyzed. Finally，the effectiveness of the results through simulation was validated.

The stability analysis of power system transient voltage，power angle，and frequency is often based on short-time-scale electromechanical transient simulation，which requires a relatively accurate large-scale simulation model，which not only has low simulation efficiency but also takes a long time，thus giving rise to the demand for dynamic equivalence of large power grids. However，as the proportion of new energy increases，the power system gradually presents some unique characteristics of new power systems，with more significant differences in system inertia，frequency spatiotemporal distribution，and frequency modulation resource distribution. Conventional dynamic equivalence methods based on slow coherence theory are gradually difficult to ensure accuracy. To solve these problems，based on previous work，a large power grid dynamic equivalence method based on random forest algorithm was proposed. First，the large power system was divided into the study area and the external area. Then the external area on the opposite side of the study area tie line was equivalent to several nonlinear dynamic loads controlled by the random forest algorithm. The random forest algorithm was trained using the original model tie line's voltage/reactive power and frequency/active power relationships. A joint simulation model based on PSS/E and Matlab platform was established to achieve equivalent simplified electromechanical transient simulation，and Python environment was used to achieve information exchange and simulation control between them. Simplified results for the Northeastern United States power grid was presented and compared them with existing methods. The results show that the proposed method can effectively balance simulation accuracy and control stability.

In order to reduce the loss of electric energy in the process of energy conversion and improve the energy efficiency of aluminum air battery，an energy efficiency model based on the internal resistance characteristics of aluminum air battery was established，and the variations of operating conditions （operating temperature，electrolyte concentration），internal resistance characteristics，output characteristics and energy efficiency were studied. In order to improve the energy efficiency of aluminum air battery，an improved pollination algorithm was adopted to obtain the optimal working temperature and electrolyte concentration under constant current density output. The validity of the model and method was verified by simulation and experiment. The results show that the energy efficiency can be improved by co-optimizing the operation conditions，and the total internal resistance can be reduced and the output performance can be improved by increasing the energy efficiency.