Evolved Bat Algorithm for Solving the Economic Load Dispatch Problem

被引：9

作者：

Dao, Thi-Kien ^{[1
]}

Pan, Tien-Szu ^{[1
]}

Trong-The Nguyen ^{[2
]}

Chu, Shu-Chuan ^{[3
]}

机构：

[1] Natl Kaohsiung Univ Appl Sci, Dept Elect Engn, Kaohsiung 807, Taiwan

[2] Haiphong Private Univ, Fac Informat Technol, Haiphong, Vietnam

[3] Flinders Univ S Australia, Sch Comp Sci Engn & Math, Adelaide, SA, Australia

来源：

GENETIC AND EVOLUTIONARY COMPUTING | 2015年 / 329卷

关键词：

Evolved Bat Algorithm; Economic Load Dispatch; Particle Swarm Optimization; Genetic Algorithm; UNIT COMMITMENT;

D O I：

10.1007/978-3-319-12286-1_12

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Economic Load Dispatch (ELD) is one of the important optimization tasks, which provides an economic condition for the power systems. In this paper, Evolved Bat Algorithm (EBA) as an evolutionary based approach is presented to solve the constraint economic load dispatched problem of thermal plants. The output generating power for all the power-generation units can be determined by the optimal technique for transmission losses, power balance and generation capacity, so that the total constraint cost function is minimized. A piecewise quadratic function is used to show the fuel cost equation of each generation unit, and the B-coefficient matrix is used to represent transmission losses. The systems with six units and fifteen units of thermal plants are used to test the demonstration of the solution quality and computation efficiency of the feasibility of the application of the Evolved Bat Algorithm for ELD. The experimental results compared with the genetic algorithm (GA) method for ELD, and with the particle swarm optimization (PSO) method for ELD, show that the applied EBA method for ELD can provide the higher efficiency and accuracy.

引用

页码：109 / 119

页数：11

共 19 条

[11] Evolutionary Algorithms for Constrained Parameter Optimization Problems [J].