Title :
Support vector machine inverse control for an energy storage inverter
Author :
Lixia Lv; Tengyi Zhu; Weiliang Liu; Changliang Liu; Peng Huang; Yufang Wang
Author_Institution :
State key laboratory of Alternate Electrical Power System with Renewable Energy Sources, Baoding, China
Abstract :
A control strategy is established to solve the difficulties in obtaining an accurate model when controlling an energy storage inverter. The inverse control model is constructed based on the Support Vector Machine (SVM) regression theory, and combined with the PI control to build the complex control system. Firstly, it introduces a SVM regression theory and an inverse control method. Then it describes the structure and implementation of the control strategy in the system. At last, the simulation is running under different conditions in Simulink, and compares with the PI control, the results prove the SVM method is feasible.
Keywords :
"Support vector machines","Voltage control","Inverters","Energy storage","Compounds","Pi control"
Conference_Titel :
Natural Computation (ICNC), 2015 11th International Conference on
Electronic_ISBN :
2157-9563
DOI :
10.1109/ICNC.2015.7377970