Neural Network pada Koordinasi PSS dan TCSC untuk Meningkatkan Kestabilan Sistem Tenaga Terinterkoneksi
Abstract: This paper develops
a design procedure for adaptive coordination among power system damping
controllers (i.e. power system stabilizers and supplementary damping controller
of thyristor-controlled series capacitor) for improving the stability of an
interconnected electric power system. The design is based on the use of neural
network which identifies the optimal controller parameters online. The inputs
to the neural network include the active- and reactive- power of the
synchronous generators which represent the power loading on the system, and
elements of the reduced nodal impedance matrix for representing the power
system configuration. The neural network-based adaptive controller is trained
offline with a wide range of credible power system operating conditions and configurations.
The controller parameters obtained from the trained neural network are verified
by both eigenvalue calculations and time-domain simulations, which confirms
that good dampings of the eletromechanical modes and stability are achieved.
Penulis: Rudy Gianto, Kho Hie
Khwee
Kode Jurnal: jptlisetrodd160435
