• DocumentCode
    230102
  • Title

    Performance study of solid state transformer applying BP artificial neural network PID regulator

  • Author

    Qingshan Wang ; Deliang Liang ; Jinhua Du

  • Author_Institution
    State Key Lab. of Electr. Insulation & Power Equip., Xi´an Jiaotong Univ., Xi´an, China
  • fYear
    2014
  • fDate
    22-25 Oct. 2014
  • Firstpage
    2440
  • Lastpage
    2444
  • Abstract
    On the basis of its working principle and topology, a mathematical model of three-phase AC-DC-AC-type solid state transformer is built. The control strategies of the AC-DC rectifier, DC-DC converter and DC-AC inverter are studied respectively. Due to the nonlinearity and time-varying uncertainty in a SST system, it is difficult to get a precise model, resulting in the unsatisfactory control results gained via adopting the traditional PID regulator. To enhance the robustness and adaptability of the SST system, a neural network PID controller is designed which modifies the proportional coefficient, integral coefficient and differential coefficient in the real-time online adjustment process. A simulation model is constructed based on Simulink and the results show that the SST model can achieve unit input power factor, constant output voltage and stability against load variation and grid disturbance.
  • Keywords
    DC-DC power convertors; invertors; neurocontrollers; power factor; power transformers; rectifiers; stability; three-term control; BP artificial neural network PID regulator; SST system; Simulink; ac-dc rectifier; constant output voltage; dc-ac inverter; dc-dc converter; differential coefficient; integral coefficient; mathematical model; nonlinearity; proportional coefficient; real-time online adjustment process; simulation model; stability; three-phase ac-dc-ac-type solid state transformer; time-varying uncertainty; unit input power factor; working principle; Inverters; Rectifiers; Regulators; Space vector pulse width modulation; Vectors; Voltage control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical Machines and Systems (ICEMS), 2014 17th International Conference on
  • Conference_Location
    Hangzhou
  • Type

    conf

  • DOI
    10.1109/ICEMS.2014.7013915
  • Filename
    7013915