This research focused on the separation and calculation of electromagnetic losses in semi-direct drived permanent magnet wind generators（SDDPMWG）.Firstly，analytical method for calculating core loss of motor considering harmonic current was derived based on the Bertotti method. The eddy current loss of permanent magnet was obtained by analyzing axial and tangential components of the eddy current density of permanent magnet. The analytical methods for calculating DC copper loss，AC copper loss，and circulating current loss of the stator winding were also analyzed. Secondly，the changes of flux density over time in 6.5 MW SDDPMWG were analyzed according to finite element method. The spatial and temporal harmonics of flux density in the core were abundant. The impact of electromagnetic frequency on core loss of generator was calculated and analyzed. Then the relationship between eddy current loss of permanent magnet and electromagnetic frequency in 6.5 MW SDDPMWG was studied. Eddy current loss of permanent magnet increases with the increase of electrical frequency.Finally，finite element method and theoretical method were combined to calculate winding DC loss，AC loss and circulating current loss of 6.5 MW SDDPMWG quantitatively. The winding AC loss and circulating current loss are big.The research results can be effectively used for electromagnetic loss separation calculation of SDDPMWG. It can also provide support for the development of high-performance and low-cost SDDPMWG.

High-precision power converters are core components of ultra-precision motor motion control systems.Their output current harmonic distortion can cause unnecessary positioning fluctuations in ultra-precision motors，severely impacting the precision control system.Total harmonic distortion is an important index in high-performance precision control fields. A class of dual-buck topologies with no dead-time characteristics can eliminate the current distortion caused by dead-time in traditional bridge topologies and output high-quality，stable waveforms. To further improve the output current harmonic distortion of a class of dual-buck topologies，the sources of harmonic distortion in a class of dual-buck topologies were first clarified.For the harmonic distortion issues introduced by the power conversion stage and control system of a class of dual-buck topologies，the characteristics of low harmonic distortion a class of dual-buck topologies were summarized.The mechanisms of suppressing harmonic distortion by different control methods were revealed，and the relationship between various modulation strategies and harmonic distortion was studied. Finally，specific application scenarios for low-distortion a class of dual-buck converters were summarized，and reference directions for their future development were provided.

A brake unit based on IGCT was designed for different applications of frequency converter in industrial scenes，especially the medium voltage frequency conversion system without feedback function. IGCT was used as the main power device，and the parameters and characteristics of IGCT was analyzed. According to the common topology of NPC medium voltage inverter in the market，the matching circuit of brake unit was designed，and the working principle of the system was described. In terms of device loss，the junction temperature of the power device was evaluated，and the water cooling circuit and the press assembly structure were designed. In order not to affect the midpoint balance of the DC bus voltage，an independent software control method was designed.Finally，the medium voltage brake unit designed has been applied to the occasion of rolling metal composite material in the indμstrial field，which confirmed the feasibility of the design scheme.

To tackle the issues of low execution efficiency and poor fault tolerance in traditional fault localization methods for active distribution networks using swarm intelligence optimization algorithms，a two-stage fault location method was introduced based on the SSA-RF algorithm and cosine similarity. Firstly，the fault current state equation was used to create a fault feature database of the target distribution network by stochastically simulating single-point and multi-point faults. Next，an enhanced random forest（RF）classification model that integrates the sparrow search algorithm（SSA）was introduced. Through model training，a high-dimensional mapping correlation between the fault current direction matrix and the line segment containing the fault point was established.This trained SSA-RF classification model was utilized for the initial localization of the faulted line segment.Subsequently，cosine similarity of fault current direction information of neighboring segmented lines within the identified segment was computed for precise fault location. Experimental results on the modified IEEE 33-node test distribution network demonstrate that the proposed two-stage fault locatlizaion method achieves superior accuracy and anti-interference capabilities compared to fault location methods based on swarm intelligent optimization algorithms.

Accurate short-term electrical load forecasting is of great significance for the design and optimization scheduling of integrated energy systems（IES）. However，the load data in real integrated energy systems are low-quality and fluctuating，so the forecasting accuracy of existing prediction models is low. A short-term electrical load forecasting method based on attention-based long short-term memory（AT-LSTM）and Stacking learning was proposed. Under the framework of Stacking ensemble learning，AT-LSTM，random forest and decision tree were ensembled to forecast short-term electrical load which can make up for the low prediction accuracy of a single model. Based on the exploratory analysis results of data，the data feature engineering model was constructed to input features，and this prediction method was used for short-term electricity load prediction. The experimental results of the integrated energy system in Beijing show that compared to other algorithms，the proposed method has a maximum prediction error reduction of 24.8%.

A K-means clustering algorithm was proposed and a conditional Wasserstein generative adversarial network with gradient penalty（CWGAN-GP）to address the problem of imbalanced photovoltaic generation data caused by the low occurrence probability of extreme weather. A prediction approach combining bidirectional long short-term memory（BFLSTM）with convolutional neural network was introduced and incorporating channel attention mechanism to enhance the PV power prediction performance by integrating spatio-temporal features and dynamically adjusting the importance of feature channels. Firstly，correlation analysis and K-means algorithm were utilized to select and label various environmental factors. Then，extreme weather labels with fewer samples after clustering were selected，and CWGAN-GP was used for data augmentation.Finally，the augmented dataset was used to train the CNN-SE-BiLSTM prediction model for PV power prediction under extreme weather conditions.Simulation modeling was conducted using data from a certain PV power station，and the results demonstrate that augmenting the original extreme weather training set with CGAN-GP helps improve the prediction accuracy of the model. Moreover，CNN-SE-BiLSTM shows higher prediction accuracy among five weather categories compared to other traditional models，indicating that the proposed method is suitable for ultra-short-term photovoltaic power prediction.

In order to solve the problem of parameter estimation in the high-performance control of squirrel cage asynchronous motor，a method for joint parameter identification of asynchronous motors with dual models based on improved whale algorithm was proposed. This method can effectively identify the stator resistance，the rotor resistance，mutual inductance and leakage inductance. In order to improve the identification accuracy of the algorithm，the nonlinear convergence factor was adopted，and the ideas of chaotic reverse learning，simulated annealing and adaptive mutation perturbation were integrated to overcome the shortcomings of the whale algorithm，which relied on the initial population，was easy to fall into local optimum，and had low convergence accuracy. Moreover，combining the advantages of the two traditional motor models，an improved dual-model joint identification was proposed，which further improves the accuracy of parameter identification. Based on this model，the improved whale algorithm was compared with the other two algorithms for motor parameter identification，and the experimental results show that the improved algorithm has high recognition accuracy，which proves the feasibility of applying the algorithm to identify the parameters of the squirrel cage asynchronous motor，and is of great significance for improving the control performance of the squirrel cage asynchronous motor.

The grid frequently exhibits weak grid characteristics because the impedance fluctuation range of the collector network is broad in high permeability distributed generation system. The coupling relationship between the phase-locked loop and the grid impedance leads to desynchronizing between the grid-following（GFL）converter and grid，which seriously threatens the stability of the system. However，the slow power response of grid-forming（GFM）converter is contradictory to the maximum power point tracking of source side，and the economy is poor. Consequently，in order to increase the grid-connected reliability of the system，some units are necessary to be configured flexibly，which will switch to the GFM mode. Concentrating on the grid-connected converters，a dual-mode adaptive flexible switching control strategy for distributed energy was proposed considering friendly interaction between grid and converters to maximize the utilization of new energy under the premise of system stability. The grid impedance identification algorithm based on non-characteristic harmonic injection was applied to sense the power grid strength，and the control strategy was adaptively switched according to the strength of the grid. Under the circumstance of robust grid，the constant power control method was adopted，which can quickly respond to the maximum power point instruction and improve the utilization rate of renewable energy. During the weak grid，converters flexibly switch to the virtual synchronous generator（VSG）control strategy to enhance inertia and damping support capabilities，realizing the friendly interaction between converters and grid. The proposed strategy enhances the robustness of grid-connected converters during the variation of grid strength，ensuring the stable operation of the system. The effectiveness of the proposed dual-mode control strategy was validated by PLECS simulation.

The structure parameters of dual-stator permanent magnet synchronous motors（DSPMSM）were optimized with finite element method and Taguchi method at the rated point，maximum torque point，and maximum speed point，respectively，aiming at the problem of large torque ripple of DSPMSM. The influence on electromagnetic torque performance of each optimization variable was also analyzed. Then，comprehensively considering the influence degree of different variables under each operation point and the proportion of each variable's influence degree to the total influence degree，the optimal combination of variables that can balance the electromagnetic torque performance under three operation points was finally obtained. The results indicate that the comprehensive optimization design method based on Taguchi method for multiple operation points can significantly reduce torque ripple and improve the electromagnetic performance of DSPMSM.

The traditional three-phase pulse width modulation（PWM）rectifier requires six power switches.Due to the shoot-through problem between two switches on the same bridge arm，the control difficulty is increased and overall system design becomes more complicated. A half-controlled three-phase PWM rectifier topology was used to achieve a three-phase rectifier. Only three power switches were used. The three switches were controlled by the same driving signal. The driving signal was generated by a dedicated controller，and the control circuit was simple. An experimental prototype was built using SiC MOSFETs as power switches. The experimental results show that the rectifier could operate at a higher switching frequency and the inductor and the capacitor are greatly reduced，thus the volume of the rectifierand the product cost are reduced，the conversion efficiency is improved and total harmonic distortion is low.