International Journal of Electrical and Computer Engineering (IJECE)
Vol. 9, No. 2, April 2019, pp. 875~883
ISSN: 2088-8708, DOI: 10.11591/ijece.v9i2.pp875-883 875
Journal homepage: http://iaescore.com/journals/index.php/IJECE
Optimal power flow based congestion management using
enhanced genetic algorithms
Seong-Cheol Kim, Surender Reddy Salkut
Department of Railroad and Electrical Engineering, Woosong University, Republic of Korea
Article Info ABSTRACT
Article history:
Received May 12, 2018
Revised Nov 10, 2018
Accepted Dec 23, 2018
Congestion management (CM) in the deregulated power systems is germane
and of central importance to the power industry. In this paper, an optimal
power flow (OPF) based CM approach is proposed whose objective is to
minimize the absolute MW of rescheduling. The proposed optimization
problem is solved with the objectives of total generation cost minimization
and the total congestion cost minimization. In the centralized market clearing
model, the sellers (i.e., the competitive generators) submit their incremental
and decremental bid prices in a real-time balancing market. These can then
be incorporated in the OPF problem to yield the incremental/ decremental
change in the generator outputs. In the bilateral market model,
every transaction contract will include a compensation price that the buyer-
seller pair is willing to accept for its transaction to be curtailed.
The modeling of bilateral transactions are equivalent to the modifying the
power injections at seller and buyer buses. The proposed CM approach is
solved by using the evolutionary based Enhanced Genetic Algorithms
(EGA). IEEE 30 bus system is considered to show the effectiveness of
proposed CM approach.
Keywords:
Bilateral transactions
Congestion cost
Congestion management
Evolutionary algorithms
Multi-lateral transactions
Optimal power flow
Copyright © 2019 Institute of Advanced Engineering and Science.
All rights reserved.
Corresponding Author:
Surender Reddy Salkuti,
Department of Railroad and Electrical Engineering,
Woosong University,
Jayan-dong, Dong-gu, Daejeon, Republic of Korea 300718.
Email: surender@wsu.ac.kr
NOMENCLATURE
Incremental cost coefficients of i
th
generating unit.
Decremental cost coefficients of i
th
generating unit.
,
Rescheduled power outputs from preferred schedule in positive or negative side of i
th
generator.
P
Gi
Amount of power injections added at i
th
seller bus.
Lower and upper bounds for active power outputs of i
th
generator.
P
Dj
Amount of power taken at j
th
buyer bus.
S
L
max
Line flow capacity/thermal limit of L
th
transmission line.
Q
Gi
, Q
Di
Reactive power generation and demand at i
th
bus.
Lower and upper bounds for reactive power outputs of i
th
generating unit.
V
i
min
, V
i
max
Lower and upper bounds of voltages at i
th
bus.
1. INTRODUCTION
With the increasing demand for electric power all around the globe, electric utilities have been
forced to meet the same by increasing their power generation. However, the electric power that can be
transmitted between two locations on a transmission network is limited by several transfer limits such as