Model predictive control （MPC） is an effective control strategy for permanent magnet synchronous generators （PMSG） due to its fast dynamic response and multi-objective optimization capabilities. However，MPC relies on accurate system models and sensor measurements. In practical conditions，parameter mismatch caused by PMSG parameter variations and sensor measurement noise can deteriorate the control performance of MPC. Robust predictive control based on extended state observer （ESO） can effectively deal with parameter mismatch. However，a single-gain ESO is difficult to balance parameter mismatch and measurement noise disturbance. Therefore，a robust predictive control method based on hybrid cascade parallel ESO （CPESO）was proposed，which used multiple sub-ESOs in series and parallel to weight system disturbances and observed values for noise suppression. This method can effectively balance parameter mismatch and measurement noise suppression. Finally，under conditions with parameter mismatch and measurement noise，experiments were conducted on a three-level PMSG test bench to verify the effectiveness of the proposed method.

The traditional technical line loss prediction method of low voltage station area has some problems，such as relatively extensive calculation，requiring underlying physical topology，and relying on influence characteristic data. In recent years，a technical line loss and meter error joint estimation technical route based on the principle of conservation of electric energy in station area has been formed，but there are still some problems of difficult model solving and long data requirement period. In order to achieve accurate estimation of technical line loss in low voltage station area，the correlation between daily technical line loss and energy supply was further analyzed on the basis of the existing joint estimation route，and the original model was optimized considering those users with small energy consumption have little influence on the model，and the technical line loss was solved based on gradient descending convex optimization algorithm. Finally，6 759 stations in a certain area were used to calculate the technical line loss. Compared with the traditional algorithm，the assignment accuracy of the proposed method reaches 98%，and is significantly improved.

In the background of a high proportion of new energy source connected to grid，the phenomenon of new energy interface inverters being connected to the grid through long-distance AC lines is becoming increasingly significant. The traditional vector controlled weak grid connected voltage source converter （VSC） based on phase locked loop （PLL） synchronization is prone to PLL synchronization instability. To improve the PLL synchronization stability of weakly connected VSC，an analytical model to reveal the PLL synchronization instability mechanism of weakly connected VSC was established. Through theoretical analysis，the influence of the dynamic coupling characteristics of PLL and different time scale control links on the PLL synchronization instability mechanism was revealed. Based on the theoretical analysis results，a PLL dynamic compensation control strategy suitable for multiple time scales was designed to improve the PLL synchronization stability of weakly connected VSC. The simulation results based on Matlab/Simulink verify the correctness of the theoretical analysis and the effectiveness of the compensation control strategy.

Wind turbine condition monitoring and wind power prediction both rely heavily on power curves. Firstly，to increase the modeling accuracy of wind turbine power curves，the random forest technique was used to screen the important variables that influence wind energy capture ability. Then，the screened variables were fed into the improved Gaussian process（GP） model，which improved computational efficiency. Finally，four separate metrics were used to evaluate the model's correctness，and the entropy weight approach was used to resolve any potential conflicts between the metrics，resulting in a comprehensive assessment metric that measured the quality of the power curve model. The suggested approach's effectiveness was validated using supervisory control and data acquisition （SCADA） data from a wind farm in the United Kingdom，and the findings reveal that the proposed method improves model accuracy when compared to the current six types of conventional methods.

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.

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.

In order to solve the problem that the time-of-use price is not taken into account in the calculation of the peaking cost in the case of a large number of renewable energy sources，a method of calculating the peaking cost of power system with time-of-use price was proposed. First，the key scenarios of power grid peak regulation were obtained，and the technical cost characteristic boundaries of various peak regulation resources were determined. Second，according to typical daily new energy and load characteristics，taking the minimum total peaking cost of the power system as the objective function，taking into account the technical output of thermal power units，charging and discharging characteristics of energy storage，capacity of pumped storage power station and other constraints，and taking into account the time-of-sale price factor，a quantitative model of the peaking cost of the power system was established. Finally，through solving the model，the peak load balancing cost and unit output under the optimal scheme were obtained. The actual data of Ningxia Power Grid，the first provincial power grid whose output of new energy generation exceeds the entire regional power load，was taken as an example to verify the model. The results show that the model can effectively evaluate the peaking cost and unit output in the key scenarios of power grid peak regulation.

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 increasing penetration of new energy equipment，while alleviating the environmental problems caused by fossil energy，it also increases the frequency instability of the system. Photovoltaic （PV）and other new energy equipment to participate in the grid frequency regulation is an effective way to improve the frequency stability of the power system.First，the basic principle of frequency response of synchronous machine was analyzed，the correspondence was determined which is between active output of PV power generation and primary frequency regulation and inertia response，and the virtual synchronous control strategy of PV power generation was formed.Then，based on the power-frequency correspondence relationship of primary frequency regulation，it gave the parameter adjustment method that directly corresponds to the frequency and the load shedding rate，and realized the function of primary frequency regulation. Once again，based on the inertia response minus the frequency-power correspondence relationship，it gave the inertia response minus the frequency-power correspondence relationship，which is the most effective way to improve frequency stability of power system. Once again，based on the correspondence between inertia response frequency reduction and power，the parameter setting method of inertia response load shedding rate was given，and the negative influence of inertia in the process of frequency restoration was avoided through the determination of application conditions of inertia response. Finally，the PV grid-connected model was constructed，which verified that the PV load shedding operation has the ability to participate in the frequency regulation of the power grid.