Research On Optimal Control Algorithm Of Power Electronic Transformer Based On Improved PSO

The development of renewable energy is the inevitable way to solve the global energy shortage.Distributed power supplies and AC/DC microgrids are the research hotspots of renewable energy pooling and utilisation in the current era.In order to realise the flexible conversion of electrical energy and voltage levels,AC-DC microgrids need to rely on power electronic transformers(PETs),which has led to the creation of power electronic transformers(PETs).In view of this,this paper presents an in-depth study of PET control strategies,with a view to laying a theoretical foundation for the widespread application of PETs in microgrids.This paper focuses on completing the following research:1.To summarise the current status of research related to three key issues in the research process of this paper: control strategies for power electronic transformers,particle swarm algorithms and cascade system stability.2.The AC/DC/AC type PET is selected as the object of study.Topological analysis and mathematical modelling are carried out for the input stage,isolation stage and output stage,while control strategies are established for each stage of the converter,in which a double closed-loop control strategy is used for the input stage rectifier link with an external voltage loop and an internal current loop,a single phase-shifting control strategy is used for the isolation stage double active full-bridge DC/DC converter,and a control strategy based on a virtual synchronous generator is used for the isolation stage inverter link.3.An optimal control strategy for PET systems is established.In view of the fact that the control effect of the control strategy depends on the adjustment of the controller parameters,and that the traditional method of adjusting the controller parameters needs to be based on engineering experience and is time-consuming,this paper proposes an improved Particle Swarm Optimization(PSO)algorithm to optimize the controller parameters.The effectiveness of the improved PSO algorithm in the process of parameter optimisation is first verified,and then introduced into the optimization of the controller parameters of each link of the PET.The above designs are combined to form an optimised control strategy for the PET system.4.The PET machine simulation model is built in MATLAB,and inductive load simulation experiments are carried out on the PET machine system.To verify the immunity of the system,input voltage disturbance,load disturbance and reactive power disturbance are simulated and analysed respectively.Simulation results show that,compared with the PET system using the traditional way of adjusting the controller parameters,the PET system based on the improved PSO optimal control algorithm can reduce the dynamic adjustment time by 0.02 s,increase the net-side output voltage RMS by 3.46 V and reduce the harmonic distortion rate by 1.49% under inductive load conditions.In the event of a 10% increase in input voltage disturbance,the networkside output voltage mutation is reduced by 3.2% and the steady-state error is reduced by 0.4V.In the event of a load disturbance,the output voltage can be guaranteed to be stable,while the maximum steady-state error of the output current is reduced by 3.48 A.In the event of a reactive power disturbance,the output voltage is guaranteed to be stable and the maximum output current fluctuation is reduced by 14.62 A,while active power,reactive power and system frequency are realised.In case of reactive power disturbance,the output voltage is stable and the maximum output current fluctuation is reduced by 14.62 A.