Title :
A synchronous generator stabilizer design using neuro inverse controller and error reduction network
Author :
Park, Young-Moon ; Hyun, Seung-Ho ; Lee, Jin-Ho
Author_Institution :
Dept. of Electr. Eng., Seoul Nat. Univ., South Korea
fDate :
11/1/1996 12:00:00 AM
Abstract :
A neuro power system stabilizer (PSS) is developed for multimachine power systems. Each machine is identified in its inverse relation by an artificial neural network (inverse dynamics neural network (IDNN)) offline, which is used as a local inverse controller. The control error due to the interactions between generators is predicted and compensated through another network called the error reduction network (ERN). The ERN consists of several IDNNs in a linear combination form. In most neurocontrollers, two neural nets are required, one for system emulation, the other for control. In the proposed controller, the only network requiring training is the IDNN. Simulations are performed on two typical cases: an unstable single-machine power system of nonminimum phase, and a multimachine power system
Keywords :
control system analysis; control system synthesis; learning (artificial intelligence); machine control; machine theory; neurocontrollers; power system control; power system stability; synchronous generators; control design; control error compensation; control simulation; error reduction network; inverse dynamics neural network; multimachine power systems; neuro inverse controller; neuro power system stabilizer; synchronous generator stabilizer design; training; Artificial neural networks; Control systems; Error correction; Neural networks; Power engineering and energy; Power system dynamics; Power system simulation; Power systems; Synchronous generators; Systems engineering and theory;
Journal_Title :
Power Systems, IEEE Transactions on