World Academy of Science, Engineering and Technology
Published August 1, 2016 | Version 10005539
Journal article Open

Stability Enhancement of a Large-Scale Power System Using Power System Stabilizer Based on Adaptive Neuro Fuzzy Inference System

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Description

A large-scale power system (LSPS) consists of two
or more sub-systems connected by inter-connecting transmission.
Loading pattern on an LSPS always changes from time to time and
varies depend on consumer need. The serious instability problem is
appeared in an LSPS due to load fluctuation in all of the bus. Adaptive
neuro-fuzzy inference system (ANFIS)-based power system stabilizer
(PSS) is presented to cover the stability problem and to enhance
the stability of an LSPS. The ANFIS control is presented because
the ANFIS control is more effective than Mamdani fuzzy control in
the computation aspect. Simulation results show that the presented
PSS is able to maintain the stability by decreasing peak overshoot
to the value of −2.56 × 10−5 pu for rotor speed deviation Δω2−3.
The presented PSS also makes the settling time to achieve at 3.78
s on local mode oscillation. Furthermore, the presented PSS is able
to improve the peak overshoot and settling time of Δω3−9 to the
value of −0.868 × 10−5 pu and at the time of 3.50 s for inter-area
oscillation.

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References

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