Dynamic Stability Enhancement of Power Systems Using Neural-Network Controlled Static-Compensator
Abstract: This paper aims at
enhancement of dynamic stability of power systems using artificial neural
network (ANN) controlled static VAR compensator (SVC). SVC is proven the fact
that it improves the dynamic stability of power systems apart from reactive
power compensation; it has multiple roles in the operation of power systems.
The auxiliary control signals to SVC play a very important role in mitigating
the rotor electro-mechanical low frequency oscillations. Artificial neural
network based controller is designed using the generator speed deviation, as a
modulated signal to SVC, to generate the desired damping, is proposed in this
paper. The ANN is trained using conventional controlled data and hence replaces
the conventional controller. The ANN controlled SVC is used to improve the
dynamic performance of power system by reducing the steady-state error and for
its fast settling. The simulations are carried out for multi-machine power
system (MMPS) at different operating conditions.
Key words: artificial neural network, dynamic stability, FACTS, power system,
static VAR compensator
Author: D Harikrishna D
Harikrishna, N V Srikanth N V Srikanth
Journal Code: jptkomputergg120020
