Congestion management using multiobjective particle swarm optimization

被引：154
|
作者：
Hazra, Jagabondhu [1 ]
Sinha, Avinash K. [1 ]
机构：
[1] Indian Inst Technol Kharagpur, Dept Elect Engn, Kharagpur, W Bengal, India
来源：
IEEE TRANSACTIONS ON POWER SYSTEMS | 2007年 / 22卷 / 04期
关键词：
congestion management; generator rescheduling; multiobjective optimization; pareto optimality; particle swarm optimization;
D O I：
10.1109/TPWRS.2007.907532
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 paper presents an effective method of congestion management in power systems. Congestions or overloads in transmission network are alleviated by generation rescheduling and/or load shedding of participating generators and loads. The two conflicting objectives 1) alleviation of overload and 2) minimization of cost of operation are optimized to provide pareto-optimal solutions. A multiobjective particle swarm optimization (MOPSO) method is used to solve this complex nonlinear optimization problem. A realistic frequency and voltage dependent load flow method which considers the voltage and frequency dependence of loads and generator regulation characteristics is used to solve this problem. The proposed algorithm is tested on IEEE 30-bus system, IEEE 118-bus system, and Northern Region Electricity Board, India (NREB) 390-bus system with smooth as well as nonsmooth cost functions due to valve point loading effect.
引用
收藏
页码：1726 / 1734
页数：9
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