Iteration particle swarm optimization procedure for economic load dispatch with generator constraints

被引:79
作者
Safari, A. [1 ]
Shayeghi, H. [2 ]
机构
[1] Islamic Azad Univ, Ahar Branch, Tehran, Iran
[2] Univ Mohaghegh Ardabili, Tech Engn Dept, Ardebil, Iran
关键词
Iteration particle swarm optimization; Economic load dispatch; Prohibited operating zone; Ramp rate limits; ALGORITHM; SYSTEM;
D O I
10.1016/j.eswa.2010.11.015
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, iteration particle swarm optimization (IPSO) has been applied to determine the feasible optimal solution of the economic load dispatch (ELD) problem considering various generator constraints. Many realistic constraints, such as ramp rate limits, generation limitation, prohibited operating zone, transmission loss and nonlinear cost functions are all considered for practical operation. The performance of the classical particle swarm optimization (CPSO) greatly depends on its parameters, and it often suffers the problem of being trapped in local optima. A new index named, Iteration Best, is incorporated in CPSO to enrich the searching behavior, solution quality and to avoid being trapped into local optimum. Two test power systems, including 6 and 15 unit generating, are applied to compare the performance of the proposed algorithm with PSO, chaotic PSO, hybrid GAPSO, self organizing hierarchical PSO (SOH_PSO) methods. The numerical results affirmed the robustness and proficiency of proposed approach over other existing methods. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:6043 / 6048
页数:6
相关论文
共 21 条
[1]   A particle-swarm-based approach of power system stability enhancement with unified power flow controller [J].
Al-Awmi, Ali T. ;
Abdel-Magid, Y. L. ;
Abido, M. A. .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2007, 29 (03) :251-259
[2]  
ALDER RB, 1977, IEEE T POWER APPL SY, V96
[3]  
[Anonymous], 2009, 2009 6 INT C EL ENG
[4]  
[Anonymous], 2004, Wiley InterScience electronic collection.
[5]   Chaotic particle swarm optimization for economic dispatch considering the generator constraints [J].
Cai Jiejin ;
Ma Xiaoqian ;
Li Lixiang ;
Peng Haipeng .
ENERGY CONVERSION AND MANAGEMENT, 2007, 48 (02) :645-653
[6]   Self-organizing hierarchical particle swarm optimization for nonconvex economic dispatch [J].
Chaturvedi, K. T. ;
Pandit, Manjaree ;
Srivastava, Laxmi .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2008, 23 (03) :1079-1087
[7]   Particle swarm optimization to solving the economic dispatch considering the generator constraints [J].
Gaing, ZL .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2003, 18 (03) :1187-1195
[8]   A particle swarm optimization-based method for multiobjective design optimizations [J].
Ho, SL ;
Yang, SY ;
Ni, GZ ;
Lo, EWC ;
Wong, HC .
IEEE TRANSACTIONS ON MAGNETICS, 2005, 41 (05) :1756-1759
[9]   Particle swarm optimization for various types of economic dispatch problems [J].
Jeyakumar, DN ;
Jayabarathi, T ;
Raghunathan, T .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2006, 28 (01) :36-42
[10]  
Kennedy J, 1995, 1995 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS PROCEEDINGS, VOLS 1-6, P1942, DOI 10.1109/icnn.1995.488968