Ant colony optimisation for economic dispatch problem with non-smooth cost functions

被引：178

作者：

Pothiya, Saravuth ^{[2
]}

Ngamroo, Issarachai ^{[1
]}

Kongprawechnon, Waree ^{[2
]}

机构：

[1] King Mongkuts Inst Technol Ladkrabang, Fac Engn, Ctr Excellence Innovat Energy Syst, Bangkok 10520, Thailand

[2] Thammasat Univ, Sch Commun Instrumentat & Control, Sirindhorn Int Inst Technol, Pathum Thani, Thailand

来源：

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS | 2010年 / 32卷 / 05期

关键词：

Ant colony optimisation; Economic dispatch problem; Genetic algorithm; Particle swarm optimisation; Tabu search; GENETIC ALGORITHM; TABU SEARCH; UNITS;

D O I：

10.1016/j.ijepes.2009.09.016

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 novel and efficient optimisation approach based on the ant colony optimisation (ACO) for solving the economic dispatch (ED) problem with non-smooth cost functions. In order to improve the performance of ACO algorithm, three additional techniques, i.e. priority list, variable reduction, and zoom feature are presented. To show its efficiency and effectiveness, the proposed ACO is applied to two types of ED problems with non-smooth cost functions. Firstly, the ED problem with valve-point loading effects consists of 13 and 40 generating units. Secondly, the ED problem considering the multiple fuels consists of 10 units. Additionally, the results of the proposed ACO are compared with those of the conventional heuristic approaches. The experimental results show that the proposed ACO approach is comparatively capable of obtaining higher quality solution and faster computational time. (C) 2009 Elsevier Ltd. All rights reserved.

引用

页码：478 / 487

页数：10

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