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
Link To Document