A rotor position detection strategy based on virtual neutral point was proposed to realize position sensorless control of BLDC motor. Through the three-phase terminal voltage with the same value of three resistances star connection to construct a virtual neutral point，the relationship between the virtual neutral point voltage and commutation time of BLDC motor was analyzed. A conclusion was drawed that the moment when the virtual neutral point voltage through the DC bus midpoint is the zero-crossing time of the back electromotive force （BEMF），and the operation of the motor in each state，the effectiveness of zero-crossing signal of BEMF was further analyzed. The scheme was further verified by experiments，and the output of zero-crossing signal was realized by comparator. Compared with the conventional terminal voltage detection method，the system reduced two comparison detection circuits and has no phase shift. Experimental results show that the position of zero-crossing signal can be accurately determined by using this strategy，and the phase error caused by traditional BEMF method can be avoided.

Active power filters（APF）are widely used for dynamic compensation of power system harmonic. However，under weak grid conditions，the interaction between APF，nonlinear loads and grid impedance can easily lead to the stability issue of harmonic oscillation around the compensation frequency，resulting in the fault of harmonic compensation and further deterioration of the system's power quality. Through small-signal modelling of the loop，the harmonic oscillation mechanism in APF system under weak grid conditions was revealed，and an active damping scheme based on inductor current feedback was proposed to suppress harmonic oscillation according to the conclusion of stability analysis，which ensures the stable harmonic compensation capability of APF under weak grid conditions. The effectiveness of the proposed scheme was verified by PLECS time-domain simulations and hardware platform experiments.

When the permanent magnet assisted synchronous reluctance motor（PMaSynRM）runs at high-speed with flux-weakening control，the DC bus voltage utilization is not high，and the efficiency and torque output capacity of the motor are low. Therefore，a flux-weakening control strategy of permanent magnet assisted synchronous reluctance motor based on hexagonal trajectory was proposed. Firstly，based on the d-q axis equivalent circuit of the permanent magnet assisted synchronous reluctance motor，the voltage and current constraints of the flux-weakening process were derived，and the root cause of the flux-weakening control to improve the speed regulation ability of the motor was proved. Secondly，in order to give full play to the advantages of high-power density under high-speed operation of permanent magnet assisted synchronous reluctance motor，the over-modulation algorithm was derived. It was applied to the flux-weakening operation of permanent magnet assisted synchronous reluctance motor to achieve higher DC bus voltage utilization. Finally，the effectiveness of the proposed method was verified by simulation.

In response to the complex working environment of pumped storage energy units，where disturbances such as temperature variations are prominent，and considering the insufficient control precision of traditional vector control for brushless doubly-fed machine（BDFM），a study was conducted on a control strategy based on linear active disturbance rejection control（ADRC）for power decoupling of BDFM.This strategy aims to mitigate disturbances，enhance control precision，improve operational characteristics，and consequently elevate the energy conversion efficiency within pumped storage energy systems.The mathematical model for BDFM in the unified coordinate system and two-phase rotating coordinate system was established.The coordinate system was determined using the power winding orientation method.The current relationship under the power winding orientation was derived，and based on this，the control winding was used to control the active and reactive power of the power winding，thereby achieving power decoupling control.To improve control performance，the speed loop and current loop were rewritten，disturbances were analyzed，state equations were formulated，an extended state observer was designed，and the control performance of the machine was enhanced using the active disturbance rejection control technique.Based on the analysis of harmonics，it is concluded that the main harmonic in the synchronous coordinate system is the 6th harmonic.To suppress specific frequency harmonics，the repetitive controller was employed.Through Simulink simulation，dynamic responses and Fourier analysis of the d-axis winding current were observed，confirming the effectiveness of the proposed active disturbance rejection power decoupling control method and harmonic suppression method.

In order to optimize the current stress of dual active bridge（DAB）converter，an improved dual phase shift （IDPS）modulation was proposed based on the traditional dual phase shift （DPS）modulation. Firstly，the working principle of IDPS modulation was introduced，its steady-state working characteristics were analyzed，and the mathematical model of current stress on transmission power was established. Then，the optimal value of current stress of IDPS modulation was obtained by using Lagrange multiplier method，and compared with traditional single phase shift（SPS） and DPS modulation methods. Finally，an experimental platform was built to verify the effectiveness of the proposed control strategy in optimizing current stress，meanwhile，the efficiency of the converter was improved.

Under digital control，the inner current loop of the LC-type inverter is affected by the control delay，which leads to the weakening of its active damping effect. Increasing the sampling control frequency can effectively reduce the negative influence of digital control delay. Furthermore，in order to suppress the high order harmonic disturbance caused by strongly nonlinear load，multiple resonant controllers are needed in the outer voltage loop. For reducing the time complexity of the outer voltage loop and increasing the quantity of the controlled harmonics，an optimal sampling digital control strategy was proposed for the current and voltage double loop control of the LC-type inverter. Specifically，the inner current loop was set to the double sampling control frequency and the outer voltage loop was set to the single sampling control frequency. The optimal sampling digital control strategy enhance the suppression ability of nonlinear load disturbance and reduce the total harmonic distortion of the output voltage while maintaining the stability margin of the inner current loop. Finally，the feasibility and effectiveness of the proposed optimal sampling digital control strategy were verified by experiments.

In traditional current protection，the effective value of current is compared with the setting value to identify the fault which is the typical protection scheme for the transmission lines of the power distribution systems. The current is calculated by the fast Fourier transform algorithm. As the calculation of the effective value of current requires a long time，the speed of the current quick break protection is reduced. In this regard，a fast current protection algorithm based on the discrete setting-value was presented to solve this problem. The main emphasis was placed on the construction of the discrete sequence of setting-value and the protection criterion. The protection startup criterion and action criterion were constructed based on comparisons between discrete sequence of setting-value and sampling-value of the current fault component. The operation characteristics and reliability of the fast current protection were analyzed. The performance of the novel fast current protection algorithm was compared with that of the conventional current protection through simulations based on PSCAD/EMTDC. The results verify that the novel fast current protection algorithm has good operation characteristics under different fault conditions.

The energy flow analysis method with both high precision and high computational efficiency is a basic tool to simulate the operation and analyze the interaction between the thermal and electric coupling systems. The traditional iterative numerical method is slow in computation，poor in computability for large-scale problems，and can only obtain the value of the state variable in discrete time series. Moreover，the traditional numerical method to solve electric power flow is not compatible with that to solve the dynamic flow of the heat network，so the alternating iterative solution is often adopted in the dynamic energy flow analysis，which makes the error spread in the iterative process. To solve the above problems，a dynamic energy flow analysis method was proposed based on holomorphic embedding for integrated electricity and heating systems. Through recursive calculation，the continuous analytic function of system state variable with respect to time was obtained. In the calculation process，the solution of electric power system and heating system was obtained jointly. The simulation results show that the maximum error between the algorithm and the Matlab solver is less than 3%，and the calculation speed is increased by more than 30%. Moreover，the algorithm can calculate the system state at any time in the dynamic process according to the holomorphic function.

To address the need of carbon emission peak and carbon neutrality target on local energy systems，an optimal expansion planning method of heat pump was proposed for regional energy stations considering the benefits from ancillary services. The method was used to support the integration of new technologies such as heat pumps into existing local energy systems. Firstly，an integrated power，gas and heating system model was developed to reflect the interactions between different energy systems. On this basis，a bi-level expansion planning model that considers the benefits of grid ancillary services was proposed，taking into account the impact of factors such as energy cost，ancillary services price，existing energy storage capacity，and carbon emission cost on the planning results. Finally，a university campus energy supply station where heat pump replaces combined heat and power units was used as an example to analyze the effects of the above factors on the expansion planning results，validating the effectiveness of the proposed method.

In order to balance the output difference between renewable energy and load in the active distribution network and reduce the budget cost and user purchase cost，an optimal dispatching method of distributed generation units in the active distribution network based on power demand side response was proposed. On the premise of power demand side response，set the optimal dispatching priority of distributed generation units，combined with the objective function established with the total generation cost of active distribution network as the minimum objective，set the node voltage，power flow process，state of charge of energy storage system and power limit constraints of flexible load in all time periods of the active distribution network dispatching cycle，on this basis，the optimal dispatching model of active distribution network distributed generation units was constructed. Finally，the improved particle swarm optimization algorithm was used to solve the model and obtain the final optimized scheduling result. The experimental results show that the proposed method can effectively balance the difference in power generation output between renewable energy and load，which not only improves the absorption capacity of active distribution networks for renewable energy，but also reduces power generation budget expenses and user purchase costs.

The integrated energy system contains adjustable resources and flexible operating modes，which to a certain extent play a supporting role in the power grid and assist in optimizing its operation. Based on this，an optimal operation model of integrated energy system considering support capacity to power grid was proposed. Firstly，the electric-heat integrated energy system（EHIES）was considered as the research object and the EHIES model was established. Secondly，considering the expected support demand of external power grid and aiming at meeting the expected support demand of external power grid，the optimal operation model of EHIES was established. Considering the complexity of the model，the Bacterial Colony Chemotaxis optimization algorithm was used to solve it. Finally，an integrated energy system in northern China was considered as an example and the effectiveness of the proposed model was verified. By adjusting the flexible operation of the EHIES，it can effectively meet the expected support needs of the external power grid and play an external support role.

In order to solve the problems of high subjective misjudgment rate and low efficiency in manual hand touch and auscultation methods for acoustic quality detection of micro motors，while taking into account the accuracy of detection results and the fast construction of detection models，a small sample machine learning detection method was proposed. Based on the physical model of micro motor transmission chain，multi-dimensional acoustic fault features were extracted，particle swarm optimization was used to optimize the core parameters of support vector machine，a small sample learning method，so as to improve the accuracy of model discrimination.The experimental results show that this method can effectively distinguish abnormal vibration and sound of micro motors，with an accuracy rate of over 95%.