DocumentCode :
3382811
Title :
Smart grid reconfiguration using simple genetic algorithm and NSGA-II
Author :
Ramaswamy, Parvathy Chittur ; Deconinck, Geert
Author_Institution :
K.U. Leuven, Leuven, Belgium
fYear :
2012
fDate :
14-17 Oct. 2012
Firstpage :
1
Lastpage :
8
Abstract :
Increased penetration of distributed generators (DGs) is one of the characteristics of smart grids. Distribution grid reconfiguration is one of the methods of accommodating more DG into the electric grid, which is illustrated with the help of a 16 node test network in this paper. The reconfiguration of the distribution grid involves changing the grid topology thereby optimizing a few objectives. In addition to the inclusion of DGs, grid reconfiguration also helps in achieving minimal power loss, minimal voltage deviation etc. In this paper the grid reconfiguration problem is formulated as an optimization problem. Simple genetic algorithm (GA) and its variant NSGA-II are used for solving the optimization problem. For a simple test system like the 16 node system discussed in this paper, simple GA is efficient enough to find the global optimum for a single objective optimization. The paper also illustrates the advantage of NSGA-II compared to simple GA when multiple objectives are considered.
Keywords :
distributed power generation; genetic algorithms; losses; smart power grids; DG; GA; IEEE 16 node system; IEEE 16 node test network; NSGA-II; distributed generator; distribution grid reconfiguration problem; electric grid topology; minimal power loss; minimal voltage deviation; optimization; simple genetic algorithm; smart grid reconfiguration; Encoding; Genetic algorithms; Linear programming; Optimization; Smart grids; Sociology; Statistics; Distribution grid; Genetic algorithm; Grid reconfiguration; NSGA-II; Optimization; Smart grid;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovative Smart Grid Technologies (ISGT Europe), 2012 3rd IEEE PES International Conference and Exhibition on
Conference_Location :
Berlin
ISSN :
2165-4816
Print_ISBN :
978-1-4673-2595-0
Electronic_ISBN :
2165-4816
Type :
conf
DOI :
10.1109/ISGTEurope.2012.6465615
Filename :
6465615
Link To Document :
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