A Solution to Unit Commitment Problem by ACO and PSO Hybrid Algorithm

Author

Xiao, Gang ; Li, Shouzhi ; Wang, Xuanhong ; Xiao, Rui

Author_Institution

Sch. of Autom. & Inf. Eng., Xi´´an Univ. of Technol.

Volume

2

fYear

0

fDate

0-0 0

Firstpage

7475

Lastpage

7479

Abstract

To solve the mixed-integer nonlinear programming problem of unit commitment in electric power system, the problem was separated into two subordinate optimization problems with integral and continuous variables first, then a new hybrid algorithm based on ant colony optimization (ACO) and particle swarm optimization (PSO) was proposed. The first step is to realize unit-scheduled problem using ACO; the second step is to solve economic dispatch (ED) in these units using PSO. In addition, some criterions are used to prevent ants from searching invalid unit status, which enhance speed and efficiency of the algorithm. Two generation scheduling systems with 5 or 10 units are tested. The simulation results demonstrate the feasibility and effectiveness of the proposed algorithm in solving unit commitment

Keywords

integer programming; nonlinear programming; particle swarm optimisation; power generation dispatch; power generation scheduling; power system economics; power system simulation; ant colony optimization; economic dispatch; electric power system; generation scheduling systems; mixed-integer nonlinear programming problem; particle swarm optimization; unit commitment problem; unit-scheduled problem; Automation; Intelligent control; Ant Colony Optimization; Economic Dispatch; Particle Swarm Optimization; Unit Commitment;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1713418

Filename

1713418