Approach for the solution of transmission congestion with multi-type FACTS devices

被引:37
|
作者
Bhattacharyya, Biplab [1 ]
Kumar, Sanjay [1 ]
机构
[1] Indian Sch Mines, Dept Elect Engn, Dhanbad, Jharkhand, India
关键词
flexible AC transmission systems; search problems; load flow control; static VAr compensators; thyristor applications; power transformers; cost reduction; power transmission economics; genetic algorithms; particle swarm optimisation; reactive power control; power transmission control; transmission congestion; multitype FACTS device; gravitational search algorithm; GSA; optimisation technique; multitype flexible AC transmission system; reactive power source; connected power network; unified power flow controller; static VAr compensator; thyristor controlled series capacitor; IEEE-30 bus system; IEEE-57 bus system; transformer tap setting arrangement; active power loss reduction; genetic algorithm; differential evolution; particle swarm optimisation technique; reactive generation control; generators line loss; POWER-FLOW CONTROLLER; OPTIMAL LOCATION; SYSTEMS; UPFC; ALGORITHM; ENHANCEMENT; OPTIMIZATION; PLACEMENT; SECURITY; IMPACT;
D O I
10.1049/iet-gtd.2015.1574
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This study presents gravitational search algorithm (GSA)-based optimisation technique for the optimum co-ordination of multi-type flexible AC transmission system (FACTS) devices with the existing reactive power sources present in a connected power network. Three types of FACTS devices: namely, unified power flow controller, static var compensator and thyristor controlled series capacitor are used in the present problem and IEEE-30 and IEEE-57 bus systems are taken as standard test systems. The existing reactive power sources are reactive generations of the generators and transformer tap setting arrangements. The main objective of the present study is to reduce active power loss, system operating cost including the cost of FACTS devices and congestion in transmission network. The result obtained with the proposed GSA-based approach is compared with the results obtained by genetic algorithm, differential evolution and particle swarm optimisation techniques. It is observed that by optimal placement of FACTS devices along with the optimal setting of the transformer tap arrangements and control of reactive generations of the generators line loss, system operating cost and transmission congestion is reduced significantly by the GSA-based method compared with other methods.
引用
收藏
页码:2802 / 2809
页数:8
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