A COMBINATION OF GENETIC ALGORITHM AND PARTICLE SWARM OPTIMIZATION FOR OPTIMAL DISTRIBUTED GENERATION LOCATION AND SIZING IN DISTRIBUTION SYSTEMS WITH FUZZY OPTIMAL THEORY

被引：49
|
作者：
Moradi, M. H. [1 ]
Abedini, M. [1 ]
机构：
[1] Bu Ali Sina Univ, Fac Engn, Dept Elect Engn, Hamadan, Iran
来源：
INTERNATIONAL JOURNAL OF GREEN ENERGY | 2012年 / 9卷 / 07期
关键词：
Distributed generation; Genetic algorithm; Location and sizing; Particle swarm optimization; Losses; Fuzzy optimal theory; DG ALLOCATION; CYCLE;
D O I：
10.1080/15435075.2011.625590
中图分类号：
O414.1 [热力学];
学科分类号：
摘要：
Distributed generation (DG) sources are becoming more prominent in distribution systems due to the incremental demands for electrical energy. Locations and capacities of DG sources have profoundly impacted on the system losses in a distribution network. In this paper, a novel combined genetic algorithm (GA)/particle swarm optimization (PSO) is presented for optimal location and sizing of DG on distribution systems. The objective is to minimize network power losses, to obtain better voltage regulation, and to improve the voltage stability within the framework of system operation and security constraints in radial distribution systems. This multi-objective optimization problem is transformed to single objective problem by employing fuzzy optimal theory. A detailed performance analysis is carried out on 33 and 69 bus systems to demonstrate the effectiveness of the proposed methodology.
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页码：641 / 660
页数：20
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