A Comparative Study of State-of-the-Art Transmission Expansion Planning Tools

Author

Sum-Im, T. ; Taylor, G.A. ; Irving, M.R. ; Song, Y.H.

Author_Institution

Sch. of Eng., Brunel Univ., Uxbridge

Volume

1

fYear

2006

fDate

6-8 Sept. 2006

Firstpage

267

Lastpage

271

Abstract

In this paper, a novel differential evolution algorithm (DEA) is applied directly to the DC power flow based model to solve the transmission expansion planning (TEP) problem. This paper presents a major development of artificial intelligent (AI) algorithms through application of a DEA to the TEP problem. The effectiveness of the proposed development is initially demonstrated via analysis of the Garver´s six-bus test system and the IEEE 25-bus test system within the mathematical programming environment of MATLAB. Analyses are performed using both a DEA and a conventional genetic algorithm (CGA) and a detailed comparative study is presented

Keywords

evolutionary computation; load flow; power transmission planning; DC power flow; DEA; Garver´s six-bus test system; IEEE 25-bus test system; MATLAB; TEP; artificial intelligent algorithm; differential evolution algorithm; mathematical programming environment; transmission expansion planning problem; Artificial intelligence; Data envelopment analysis; Load flow; MATLAB; Mathematical model; Mathematical programming; Performance analysis; Power system modeling; Power system planning; System testing; Artificial Intelligence; Differential Evolution Algorithm; Genetic Algorithm; Transmission Expansion Planning;

fLanguage

English

Publisher

ieee

Conference_Titel

Universities Power Engineering Conference, 2006. UPEC '06. Proceedings of the 41st International

Conference_Location

Newcastle upon Tyne

Print_ISBN

978-186135-342-9

Type

conf

DOI

10.1109/UPEC.2006.367757

Filename

4218686