A comparative study of state-of-the-art transmission expansion planning tools

被引：6
|
作者：
Sum-Im, T. [1 ]
Taylor, G. A. [1 ]
Irving, M. R. [1 ]
Song, Y. H. [1 ]
机构：
[1] Brunel Univ, Sch Engn & Design, Brunel Inst Power Syst, Uxbridge UB8 3PH, Middx, England
来源：
PROCEEDINGS OF THE 41ST INTERNATIONAL UNIVERSITIES POWER ENGINEERING CONFERENCE, VOLS 1 AND 2 | 2006年
关键词：
transmission expansion planning; genetic algorithm; Differential Evolution Algorithm; Artificial Intelligence;
D O I：
10.1109/UPEC.2006.367757
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
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.
引用
收藏
页码：267 / 271
页数：5
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