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.

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.

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.

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 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.

Junction-case thermal resistance has always been a highly concerned thermal parameter of power semiconductor devices，which is also the standard to weight the heat sink performance of power semiconductor devices. Heat-sink design should be considered in order to prevent device overheating damage. Therefore，accurate measurement of thermal resistance is particularly important for system heat-sink. The difficulty of devices thermal resistance measurement lies in the junction temperature measurement because it is difficult to measure junction temperature directly without destroying the devices package. Found through experiment that when the conduction voltage under small constant-current was used as the temperature-sensitive parameter，the conduction voltage and temperature had good linearity，which can be used for junction temperature measurement. Finally，the thermal resistance measurement can be completed based on the thermal resistance formula when the junction temperature was known.

In order to solve the problems of intermittent and fluctuating distributed energy，took three major physical entities in the demand response project，namely system operator，load aggregator and load end user，as the research object，the transactions between supply and demand within the power system composed by them were analyzed，and the objective conditions of the benefits of the whole system load user were considered. The factors affecting the income of load aggregators，system operators and users at the load end were proposed to combined，and an optimal bidding model with multiple types of physical entities under the market environment with the income of load aggregators as the optimization objective was constructed. In the model，the surplus and shortage of system scheduled electricity were directly connected with the power market. A typical case study shows that the optimal bidding model can effectively improve the benefits of load aggregators，and to some extent increase the benefits of load users，and indirectly improve the stability of power system.

In order to further improve the accuracy of fault identification of local abnormal factors in distribution network，a digital twin based fault identification simulation of local abnormal factors in distribution network was proposed. Through real-time acquisition of electrical parameters of distribution network operation and preprocessing，the fault feature matrix based on time series was extracted，and the multidimensional scaling （MDS）method was used to detect the abnormal physical nodes of distribution network from the reduced dimension fault features. Then，the fault section corresponding to the abnormal physical nodes was obtained according to the distribution network topology. Finally，the local abnormal factor value corresponding to each physical node was calculated with local outlier factor （LOF）algorithm，so as to obtain the fault diagnosis results and complete the accurate identification of distribution network faults. The simulation results show that the proposed method can achieve accurate identification of distribution network faults.

Combined with the current software features and the requirements for function expansion of the current test equipment engineering project，a set of test data analysis system was designed. The system includes the functions of remote test data monitoring，historical data playback，test data analysis，data prediction simulation，and test data collaborative sharing，etc. It realized the improvement of the functions of the current test and control system which transform process-oriented data management into analysis-oriented data management. The system has been applied in many test projects and provided reliable data management and analysis tools for the test. Finally，it helps users to improve the test efficiency.

To improve the quality of power distribution network parameters，an abnormal parameter identification and localization method for distribution networks based on smart meter measurements was proposed. The method transformed the nonlinear identification equation solving problem in traditional identification algorithms into the inference problem of the optimal distribution of parameters. On the basis of parameter identification，probability statistics method was used to locate abnormal parameters. Firstly，given the initial distribution of line parameters，Markov Chain Monte Carlo method was used to generate parameter samples. The parameter distribution was updated through tree estimation method and loss function. The expectation of the parameter distribution when the loss function converges was taken as the identified value of the line parameters. Secondly，the relative deviation distances of line parameters were calculated，and probability statistics method was used to judge whether the identified data are bad data or abnormal parameters. The bad data were directly eliminated. Finally，the abnormal factors causing the incorrect feedback of line parameters were analyzed to locate the abnormal parameters of the line. The identification process of parameters was demonstrated through an actual 29-node 10 kV feeder. The abnormal parameter location was carried out through an actual 97-node 10 kV feeder，proving the feasibility and effectiveness of the proposed method.