Comparison Study of Two Meta-heuristic Algorithms with Their Applications to Distributed Generation Planning

被引：9
|
作者：
Shi, Ruifeng [1 ]
Cui, Can [1 ]
Su, Kai [1 ]
Zain, Zaharn [1 ]
机构：
[1] N China Elect Power Univ, Sch Control & Comp Engn, Beijing, Peoples R China
来源：
PROCEEDINGS OF INTERNATIONAL CONFERENCE ON SMART GRID AND CLEAN ENERGY TECHNOLOGIES (ICSGCE 2011) | 2011年 / 12卷
关键词：
Distributed generation; micro-grid planning; genetic algorithm; particle swarm optimization;
D O I：
10.1016/j.egypro.2011.10.034
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 distributed micro-grid planning model has been presented to optimize the locating and the unit capacities within distributed generation (DG) micro-grid, in which wind power and photovoltaic power are taken into consideration simultaneously. Optimal power balance is achieved through minimizing the cost-effectiveness rate under given financial constraints. Both Elitism Genetic Algorithm (EGA) and Particle Swarm Optimization (PSO) are employed for comparison study with optimizing the given DG optimization model. The results have shown that EGA has outperformed PSO in the case study. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of University of Electronic Science and Technology of China (UESTC).
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页数：8
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