ABSTRACT
This
research work presented, an artificial neural network (ANN) optimization
approach for load frequency control (LFC) of hydraulic generator in a power
system by using a neural network controller to improve the stability of the
power system at transient states thereby improving efficiency of the hydraulic
generator. The comparison between a conventional Proportional Integral (PI)
controller and the proposed artificial neural networks controller was showed
that the proposed controller can generate an improved dynamic response for a
step load change. The control scheme
guarantees that steady state error of the frequency and inadvertent interchange
of tie-lines are maintained in a given tolerance limit. Neural network controller
is trained with the back propagation-through-time algorithm. The performance of
the hydraulic generator automatic generation control (AGC) is evaluated by
comparing with conventional Integral controller and the ANN. The ANN controller
gives much better results in overshoots and resettling time as compared to that
of Integral controller at load variations.
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