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January 2013 Vol.
2(1)
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Pubmed for articles by:
Hussein MT
Bader SM
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Global Advanced Research Journal of
Engineering, Technology and Innovation (GARJETI) ISSN:
2315-5124
January 2013 Vol. 2(1), pp 011-019
Copyright © 2013 Global Advanced Research Journals
Full Length Research Paper
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Electricity Distribution Scheduling For Gaza Strip
Using Genetic Algorithm
Mohammed T. Hussein1 , Wazen M. Shbair2,
Lina J. Mghari3 ,Samera M. Bader4
1Electrical
Eng. Dept., IUG, Palestine
2Computer
Eng. Dept., IUG, Palestine
3Computer
Eng. Dept., IUG, Palestine
4Computer
Eng. Dept., IUG, Palestine
Corresponding author Email:
wmshbair@iugaza.edu.ps
Accepted 07 January 2012
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Abstract |
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This paper presents a genetic algorithm based
approach to the scheduling of electricity
distribution. Gaza strip challenges shortage of
electricity power. Electricity Distribution Company
overcomes this shortage by dividing the cities into
sub-regions and providing them with electricity
power in alternating manner. But this approach
suffer from a lot of problems for regions contains
hospital and sensitive facility, also it is the lack
of systematic approach to schedule the distribution
of electricity. The proposed algorithm provides a
schedule for turn on/off transformers in sub-regions
in order to minimize the number of turn-off
transformers. For example, if the total power
consumption for a group of transformers is 15 m.W,
but the available power is 9 m.W, the genetic
algorithm provides a schedule to distribute 9 m.W on
transformed with minimum number of transformers turn
off. Also the algorithm can be adapted according to
customer power consumption in different seasons. All
constrains provided by the electricity distribution
company are considered in the genetic algorithm
design. The main advantage of the genetic algorithm
formulation is that fairly accurate results can be
obtained. The algorithm has been tested on a power
line contains 85 transformers and the number of turn
off transformer reduced to 30%, which will reduce
the duration of electricity discontinuity and
provide better service to customers.
Keywords:
Electric-Power Scheduling, Genetic algorithms,
Scheduling.
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