To address the supply-demand imbalance caused by renewable energy intermittency and load fluctuations in islanded microgrids，a two-layer optimization-based dynamic time-of-use（TOU）pricing scheduling model was proposed，aiming to enhance economic efficiency and operational stability.First，a comprehensive microgrid system model was established，integrating wind，photovoltaic，energy storage，marine energy，and diesel generators，while introducing a dynamic TOU pricing mechanism to guide user load behavior for peak shaving and valley filling.Subsequently，a two-layer optimization framework was constructed：the upper layer adjusts load distribution via dynamic pricing，and the lower layer optimizes generation dispatch and energy storage strategies to minimize operational costs，effectively resolving the limitations of traditional single-layer optimization in handling complex nonlinear constraints. Case studies demonstrate that the proposed model significantly reduces reliance on diesel generators，enhances adaptability to renewable energy fluctuations，and optimizes operational costs.The findings provide theoretical support for low-carbon scheduling of islanded microgrids，balancing economic and reliability objectives，and offer practical insights for advancing energy transition in island regions.

Accurate and efficient multi-load forecasting is of great significance for the operation control and scheduling of integrated energy system（IES），in order to improve the load forecasting effect，a integrated energy system load prediction model based on least absolute shrinkage and selection operator（LASSO）and LSTM-GRU neural network was proposed. Firstly，in order to solve the problem of complex data caused by meteorological factors in the integrated energy system，a big data selection and analysis algorithm based on LASSO was studied to select and analyze the meteorological factors to obtain an effective data set. Secondly，the long short-term memory（LSTM）neural network was used to predict the system load，and the preliminary prediction value was obtained. Subsequently，the gated recurrent unit（GRU）was used to construct the error compensation model，and the compensation value of the prediction error was obtained through the training and learning of the prediction error. Finally，by reconstructing the output of the two，a more ideal prediction result was obtained. Through the simulation of the example，the proposed prediction model has higher prediction accuracy than the traditional LSTM neural network prediction model and the LSTM model optimized by particle swarm optimizer（PSO）.

Aiming at the problem of large switching loss of modular multilevel converter（MMC），starting from the switching frequency optimization strategy，the existing switching frequency optimization strategy was improved，and the accurate analytical formula of sub-module capacitor voltage based on the real-time value of MMC transmission power was derived，so as to calculate the fluctuation range of the mean value of capacitor voltage.The dynamic retention factor was obtained by using the margin between the mean value of capacitor voltage and the engineering constraint，and the final output switching instruction was realized by the main flow of the equalization strategy.The PSCAD/EMTDC model was built based on the offshore wind power flexible engineering parameters to verify and compare the proposed strategy with the traditional strategy.The simulation results show that under the premise of meeting the requirements of the project on the fluctuation range and the imbalance index，the switching frequency of the proposed strategy is reduced by 49%~58% compared with the traditional strategy under each steady-state condition，and the switching loss is reduced by 63%~90% under each steady-state condition，and the expected loss reduction effect is achieved.

The traditional predictive current control for three-phase LCL grid connected inverters has the problems of large steady-state ripple and unstable switching frequency，which is not conducive to the quality of grid connected current and the design of filters. Therefore，an improved three vector fixed frequency predictive current control method was proposed.By applying three vectors within one control cycle，the control degrees of freedom were maximized. Firstly，an active damping method based on capacitor voltage feedback was designed to suppress resonance. Then，a duty cycle calculation method based on inverter side current deadbeat control and a seven segment symmetric pulse generation scheme were proposed. The simulation results and test results verified the superiority of the proposed method in improving dynamic performance，steady-state performance and fixing switching frequency.

Incidents such as the burning of electromagnetic voltage transformers（PT），damage to primary harmonic suppressors，and fuse tripping occur frequently in low and medium voltage distribution systems due to ferroresonance，severely affecting the safe and stable operation of the system. Therefore，through theoretical analysis and combined with field case studies，it was verified that the saturation current produced by PT saturation due to electromagnetic transient impacts from system single-phase ground faults and circuit breaker operations was the main reason for the frequent fuse tripping. Secondly，the factors influencing the saturation current of PT was analyzed and the capacity of fuses to withstand the PT saturation current was tested. The research indicates that the probability of fuse tripping could be reduced by increasing the PT's DC resistance，choosing cylindrical harmonic suppressors with relatively high knee-point voltages of their volt-ampere characteristics，and increasing the rated current of the fuses. Finally，specific recommendations for the selection of PTs，harmonic suppressors，and fuses were provided，offering reference measures for resolving the issue of frequent fuse tripping in electromagnetic voltage transformers protected by fuses.

The back-to-back active neutral-point-clamped（ANPC）converter，as the core component of the unified power flow controller of the distribution network，is widely used for the flexible closed-loop operation.However，the ANPC converter has more switching devices and commutation paths，which significantly increases the complexity of modeling.To solve the above problems，an average modeling method of the ANPC converter was proposed.The controlled source equivalent substitution method was used to replace the switching devices.The resistance-capacitance-inductance devices of other parts of the circuit were retained while averaging each branch，which greatly simplified the circuit model of the ANPC converter. On this basis，combined with the flexible control principle based on back-to-back ANPC converters，the average model of a back-to-back ANPC flexible control system was further built. By comparing the simulation results of the switch model and the average model，it was shown that the average model was consistent with the switch model in the internal branch and external characteristics，which verified the correctness and accuracy of the proposed average model and its feasibility in the application of flexible closed-loop system.

The accurate identification of hidden danger for power utilization in low-voltage substations plays an important role in improving the quality of power supply and reducing the risk of accidents.To improve the accuracy of identifying hidden danger in low-voltage substations，a low-voltage user hidden danger for power utilization identification model based on SSAE-SSA-GRU was proposed. Firstly，the user's original voltage data was normalized，and the feature parameters of the data were extracted through a stacked spares auto-encoder（SSAE）to solve the redundancy problem caused by the high dimensionality of the original voltage data. Then，the sparrow search algorithm（SSA）was introduced to optimize the hyperparameters of the gated recurrent unit（GRU）network，improving the accuracy of the model's fault diagnosis results.Finally，the performance of the established SSAE-SSA-GRU model was evaluated through numerical examples，verifying the effectiveness of the proposed method in identifying hidden danger for power utilization for low-voltage users. Compared with traditional methods for identifying abnormal electricity usage，the proposed method has good convergence and high accuracy.

In order to eliminate the problem of low inertia and large frequency fluctuation in wind power grid-connected system when power disturbance occurs，an improved virtual inertia control strategy was proposed.A cooperative control strategy of adaptive moment of inertia and damping coefficient was introduced in the main control system of wind power inverter. The energy storage static synchronous compensator（STATCOM/BESS）was used to provide the active power and reactive power required by the system. At the same time，the power output of STATCOM/BESS was adjusted according to the frequency deviation and change rate of the system. By analyzing the small signal model of virtual synchronous generator（VSG）of the fan，the setting rules of the adaptive VSG moment of inertia and damping coefficient were determined. The Matlab/Simulink simulation results show that the strategy has a more obvious effect on frequency fluctuation，and can effectively suppress the voltage drop of the fan junction point，and improve the ability of safe and stable operation of the system.

The three-core underground cable in the distribution network works in a harsh environment. Due to the influence of aging，external force，high temperature and humidity，the insulation of long-term live operation is easily damaged and causes faults. Aiming at the single-phase grounding fault of cable in distribution network，a fault location method based on the refraction-reflection characteristics of traveling wave head was proposed. Firstly，the zero-mode voltage of each line was obtained，and the arrival time of the wave head was determined. The waveform in a power frequency period after the arrival of the wave head was selected，and the main frequency of the wave head was determined. The square wave with the same frequency as the main frequency of the wave head was selected as the initial traveling wave signal，and the attenuation signal waveform at the head and end of the initial traveling wave signal after refraction of different times at this frequency was calculated.If the correlation between the corresponding data of the waveform calculated at both ends met the requirements，it was assumed that the fault point is the actual fault point. Otherwise，continue to narrow the fault interval until the correlation between the waveform data is satisfied. Simulation results show that the method can quickly and accurately realize fault distance measurement，reduce the complexity of fault distance measurement，and has strong effectiveness and practicability.

Space vector pulse width modulation（SVPWM）strategy is one of the key technologies for three-level inverters.However，conventional three-level SVPWM often experiences neutral point potential（NPP）oscillation and high switching loss when addressing the neutral point potential balancing issue.To tackle this challenge，firstly，the fundamental principles of the traditional nearest three vector（NTV）synthesis strategy and the virtual space vector pulse width modulation（VSVPWM）strategy were reviewed. And then，the drawbacks of the NTV approach based on the conventional region partitioning method was analyzed. A dynamic partitioning method was proposed to resolve the neutral point potential offset caused by conventional partitioning.Furthermore，to counteract the NPP oscillation of the NTV under high modulation，a strategy that employs a synthesis of four-effective voltage vectors was introduced. Compared to VSVPWM，the proposed strategy significantly reduced the inverter's switching loss.Ultimately，the effectiveness and superiority of the proposed algorithm were validated through experimental results.