Biogeography-Based Optimization for Different Economic Load Dispatch Problems

被引:316
作者
Bhattacharya, Aniruddha [1 ]
Chattopadhyay, Pranab Kumar [1 ]
机构
[1] Jadavpur Univ, Dept Elect Engn, Kolkata 700032, W Bengal, India
关键词
Biogeography-based optimization; economic load dispatch; genetic algorithm; particle swarm optimization; prohibited operating zone; PARTICLE SWARM OPTIMIZATION;
D O I
10.1109/TPWRS.2009.2034525
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 a biogeography-based optimization (BBO) algorithm to solve both convex and non-convex economic load dispatch (ELD) problems of thermal plants. The proposed methodology can take care of economic dispatch problems involving constraints such as transmission losses, ramp rate limits, valve point loading, multi-fuel options and prohibited operating zones. Biogeography deals with the geographical distribution of biological species. Mathematical models of biogeography describe how a species arises, migrates from one habitat to another and gets wiped out. BBO has some features that are in common with other biology-based optimization methods, like genetic algorithms (GAs) and particle swarm optimization (PSO). This algorithm searches for the global optimum mainly through two steps: migration and mutation. The effectiveness of the proposed algorithm has been verified on four different test systems, both small and large, involving varying degree of complexity. Compared with the other existing techniques, the proposed algorithm has been found to perform better in a number of cases. Considering the quality of the solution obtained, this method seems to be a promising alternative approach for solving the ELD problems in practical power system.
引用
收藏
页码:1064 / 1077
页数:14
相关论文
共 17 条
[1]  
[Anonymous], 1996, ARTIFICIAL IMMUNE SY
[2]   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
[3]   LARGE-SCALE ECONOMIC-DISPATCH BY GENETIC ALGORITHM [J].
CHEN, PH ;
CHANG, HC .
IEEE TRANSACTIONS ON POWER SYSTEMS, 1995, 10 (04) :1919-1926
[4]   Improved genetic algorithm for power economic dispatch of units with valve-point effects and multiple fuels [J].
Chiang, CL .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2005, 20 (04) :1690-1699
[5]   ENVIRONMENTALLY CONSTRAINED ECONOMIC-DISPATCH USING THE LAGRANGIAN-RELAXATION METHOD [J].
ELKEIB, AA ;
MA, H ;
HART, JL .
IEEE TRANSACTIONS ON POWER SYSTEMS, 1994, 9 (04) :1723-1729
[6]   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
[7]   Evolutionary programming based economic dispatch of generators with prohibited operating zones [J].
Jayabarathi, T ;
Sadasivam, G ;
Ramachandran, V .
ELECTRIC POWER SYSTEMS RESEARCH, 1999, 52 (03) :261-266
[8]   A Novel Coding Scheme for Practical Economic Dispatch by Modified Particle Swarm Approach [J].
Kuo, Cheng-Chien .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2008, 23 (04) :1825-1835
[9]  
Passino KM, 2002, IEEE CONTR SYST MAG, V22, P52, DOI 10.1109/MCS.2002.1004010
[10]   A new particle swarm optimization solution to nonconvex economic dispatch problems [J].
Selvakumar, A. Immanuel ;
Thanushkodi, K. .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2007, 22 (01) :42-51