Paper Info
Title
Optimal placement of Thyristor Controlled Series Compensation in power system based on Differential Evolution algorithm.
Abstract
Flexible Alternating Current Transmission Systems (FACTS) devices plays a vital role in improving the power system performance, both the static and dynamic, and enhanced the system loading capability by rerouting the power flow in the network. However, the location of these devices in the system plays a significant role to achieve such benefits, and also due to excessive cost these devices must be located optimally. This paper presents a new evolutionary optimization technique namely Differential Evolution (DE) for finding out the optimal number, the optimal locations, and the optimal parameter settings of multiple Thyristor Controlled Series Compensator (TCSC) devices to achieve a maximum system loadability in the system with minimum installation cost of these device and compare its performance with Genetic Algorithm (GA) techniques. The voltage limits for the buses and the lines thermal limits are taken as constraints during the optimization. For validate of the proposed technique simulations are performed on IEEE 6-bus and IEEE 14-bus power systems. The obtained results show that TCSC is one of the most effective series compensation devices that can significantly increase the system loadability. Also the results indicate that DE is an easy to use, fast, and robust optimization technique compared with genetic algorithm (GA). © 2011 IEEE.
Year
DOI
Venue
2011
10.1109/ICNC.2011.6022569
ICNC), 2011 Seventh International Conference
Keywords
Field
DocType
differential evolution (de),genetic algorithm (ga),loadability,power flow,tcsc,thyristors,robust optimization,evolutionary computation,genetic algorithms,genetic algorithm,optimization,differential evolution,load flow,power system
Control theory,Robust optimization,Computer science,Electric power system,Evolutionary computation,Differential evolution,Transmission system,Thyristor,Alternating current,Genetic algorithm
Conference
Volume
Issue
ISSN
4
null
2157-9555
ISBN
Citations 
PageRank 
978-1-4244-9950-2
0
0.34
References 
Authors
2
3
Name
Order
Citations
PageRank
G. I. Rashed1112.33
Yuanzhang Sun2367.68
Kaipei Liu3113.76