Distribution Network Planning Considering Distributed Generation by Genetic Algorithm Combined with Graph Theory

Due to requirements for improving energy efficiency and meeting renewable and clean energy targets, an increasing amount of distributed generation is being connected to the distribution network. In order to facilitate increasing levels of distributed generation, the medium-voltage distribution netwo...

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Bibliographic Details
Published in:Electric power components and systems Vol. 38; no. 3; pp. 325 - 339
Main Authors: Ouyang, Wu, Cheng, Haozhong, Zhang, Xiubin, Yao, Liangzhong, Bazargan, Masoud
Format: Journal Article
Language:English
Published: Philadelphia Taylor & Francis Group 01.01.2010
Taylor & Francis Ltd
Subjects:
connection
distributed generation
distribution network planning
Electric power
Electricity distribution
Electricity generation
Energy distribution
Energy efficiency
genetic algorithm
Genetic algorithms
Graph theory
Joints
Mathematical models
Meetings
Networks
Shanghai China
ISSN:1532-5008, 1532-5016
Online Access:Get full text
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Summary:Due to requirements for improving energy efficiency and meeting renewable and clean energy targets, an increasing amount of distributed generation is being connected to the distribution network. In order to facilitate increasing levels of distributed generation, the medium-voltage distribution network planning method considering distributed generation connection is proposed in this article. In addition to constraints in the conventional medium-voltage network planning model, constraints related to distributed generation connection, such as short-circuit capacity and short-circuit ratio, are considered in the new planning model. To overcome the problems of low heritability and topological infeasibility of the existing genetic algorithm applied to the distribution network planning, this article develops the efficient genetic algorithm combined with graph theory, which avoids the generation of unfeasible configurations. The efficiency of the proposed planning method is shown using a realistic region distribution network in Shanghai.
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ISSN:1532-5008
1532-5016
DOI:10.1080/15325000903273429