OPTIMASI TRANSMISSION EXPANSION PLANNING BERBASIS ALGORITMA GENETIKA
ABSTRACT: Transmission
Expansion Planning (TEP) is a basic part of power network planning that
determines where, when and how
many new transmission
lines should be
added to the
network. Its task
is to minimize
the network construction and
operational cost, while
meeting imposed technical,
economic and reliability constraints. Genetic
Algorithms (GAs) have
demonstrated the ability
to deal with
non-convex, nonlinear, mixed-integer optimization
problems, like the
TEP problem, better
than a number
of mathematical methodologies. This study is divided into two scenarios,
scenario 1 is simulated TEP without considering power losses and scenario 2
is simulated by considering the
TEP power loss.
Used AC load
flow in the
long term TEP.
The simulation is applied to the Garver 6 bus system 230 kV and 400
kV. Simulation results shows the use of
a voltage level of 400 kV is more economical than the 230 kV. TEP with scenario 1
has the initial
investment cost is
lower compared with
TEP scenario 2.
However, at the
time of implementation, scenario
2 after the 9th year have lower operational costs.
Keywords: AC
Load Flow, Genetic
Algorithm, Network Losses,
Transmission Expansion Planning, Optimization
Penulis: Ikrima Alfi, Sarjiya,
Oyas Wahyunggoro
Kode Jurnal: jptmesindd140158
