DocumentCode
1361921
Title
Genetic algorithms applied to the design of large power distribution systems
Author
Ramírez-Rosado, Ignacio J. ; Bernal-Agustín, José L.
Author_Institution
Dept. de Ingenieria Electr., Zaragoza Univ., Spain
Volume
13
Issue
2
fYear
1998
fDate
5/1/1998 12:00:00 AM
Firstpage
696
Lastpage
703
Abstract
This paper presents the application of a new genetic algorithm for the optimal design of large distribution systems, solving the optimal sizing and locating problems of feeders and substations using the corresponding fixed costs as well as the true nonlinear variable costs. It can be also applied to single stage or multistage distribution designs. The genetic algorithm has been tested with real size distribution systems achieving optimal designs in reasonable CPU times compared with respect to the dimensions of such distribution systems. On the other hand, these distribution systems present significantly larger sizes than the ones frequently found in the technical literature about the optimal distribution planning. Furthermore, original operators of the genetic algorithm have been developed in order to obtain global optimal solutions, or very close ones to them. An integer codification of the genetic algorithm has also been used to include several relevant design aspects in the distribution network optimization
Keywords
distribution networks; economics; genetic algorithms; substations; distribution network optimization; feeder optimal sizing; feeders location; fixed costs; genetic algorithms; global optimal solutions; integer codification; large power distribution systems; multistage distribution designs; optimal designs; optimal distribution planning; single stage distribution designs; substations location; substations optimal sizing; true nonlinear variable costs; Algorithm design and analysis; Cost function; Design optimization; Genetic algorithms; Optimization methods; Power distribution; Power system modeling; Power system planning; Substations; System testing;
fLanguage
English
Journal_Title
Power Systems, IEEE Transactions on
Publisher
ieee
ISSN
0885-8950
Type
jour
DOI
10.1109/59.667402
Filename
667402
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