Ant colony system based unit commitment problem with Gaussian load distribution

Author

Simon, S.P. ; Padhy, N.P. ; Anand, R.S.

Author_Institution

Dept. of Electr. Eng., Indian Inst. of Technol., Roorkee

fYear

0

fDate

0-0 0

Abstract

Ant colony system (ACS) is more suitable for hard combinatorial optimization problems. So ACS has been applied to unit commitment problem (UCP). The UCP is solved with power flow constraints. Also to make the system function in a realistic environment, white Gaussian noise (WGN) is added to the network nodes with proportional loads to the demand forecasted at each hourly stage. Multi-stage decisions give ant search competitive over other conventional techniques. The proposed model is tested on IEEE 30 bus system and has been compared with dynamic programming (DP) and branch and bound integer programming (BBIP) approaches

Keywords

Gaussian noise; combinatorial mathematics; integer programming; load distribution; load flow; power generation scheduling; white noise; Gaussian load distribution; ant colony system; unit commitment problem; Ant colony optimization; Decision making; Dynamic programming; Gaussian noise; Hydroelectric power generation; Linear programming; Power generation; Power generation economics; Space exploration; System testing; Combinatorial optimization; ant colony system; elistic ants; white gaussian noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Engineering Society General Meeting, 2006. IEEE

Conference_Location

Montreal, Que.

Print_ISBN

1-4244-0493-2

Type

conf

DOI

10.1109/PES.2006.1708997

Filename

1708997