DEPSO and Bacterial Foraging Optimization Based Dynamic Economic Dispatch with Non-Smooth Fuel Cost Functions

被引:5
作者
Vaisakh, K. [1 ]
Praveena, P. [2 ]
Rao, S. Rama Mohana [1 ]
机构
[1] AU Coll Engn, Dept Elect Engn, Visakhapatnam 530003, Andhra Pradesh, India
[2] Godavari Inst Engg &Tech, Dept Elect & Elect Engn, Rajahmandry 533294, Andhra Pradesh, India
来源
2009 WORLD CONGRESS ON NATURE & BIOLOGICALLY INSPIRED COMPUTING (NABIC 2009) | 2009年
关键词
Dynamic economic dispatc; non-smooth fuel cost function; Bacterial Foraging; particle swarm optimization; EVOLUTIONARY PROGRAMMING TECHNIQUES; DIFFERENTIAL EVOLUTION; GENETIC ALGORITHM; UNITS;
D O I
10.1109/NABIC.2009.5393632
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Dynamic Economic Dispatch (DED) problem is an optimization problem with an objective to determine the optimal combination of power outputs for all generating units over a certain period of time in order to minimize the total fuel cost while satisfying dynamic operational constraints and load demand in each interval. Recently social foraging behavior of Escherichia coli bacteria has been explored to develop a novel algorithm for distributed optimization and control. The Bacterial Foraging Optimization Algorithm (BFOA) is currently gaining popularity in the community of researchers, for its effectiveness in solving certain difficult real-world optimization problems. This article comes up with a hybrid approach involving Differential Evolution Particle Swarm Optimization (DEPSO) and BFOA for solving the DED problem of generating units considering valve-point effects. The proposed hybrid algorithm has been extensively compared with the classical approach. The new method is shown to be statistically significantly better on two test systems consisting of five and ten generating units. The results obtained through the proposed method are compared with those reported in the literature.
引用
收藏
页码:152 / +
页数:2
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