Title :
Control of advanced static VAr generator by using recurrent neural networks
Author :
Chen, Wei ; Liu, Yongqiang ; Chen, Jun ; Wu, Jie
Author_Institution :
Electr. Power Coll., South China Univ. of Technol., Guangzhou, China
Abstract :
According to the dynamic characteristic of the advanced static VAr generator (ASVG), a recurrent neural network (RNN) based inverse dynamic controller is constructed in this paper, and its training algorithm is given. Taking the single machine infinite bus power system, a three-phase short circuit is used for the test of the proposed RNN controller. Simulation results show the RNN controller can learn the inverse dynamic of a controlled power system and has better performance than the PID controller
Keywords :
neurocontrollers; power system control; recurrent neural nets; static VAr compensators; advanced static VAr generator control; inverse dynamic controller; recurrent neural networks; single machine infinite bus power system; three-phase short circuit; training algorithm; Character generation; Circuit simulation; Circuit testing; Control system synthesis; Control systems; Power system dynamics; Power system simulation; Reactive power; Recurrent neural networks; System testing;
Conference_Titel :
Power System Technology, 1998. Proceedings. POWERCON '98. 1998 International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-4754-4
DOI :
10.1109/ICPST.1998.729203
