A Parallel Implementation of Unscheduled Flow Control in Interconnected Power Systems
The unscheduled power flow problem needs to be minimized or controlled as soon as possible in a deregulated power system since the transmission systems are mostly operated at their power-carrying limits or very close to it. The time spent for simulations to determine the current states of all the sy...
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2012-01-01
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2012/376291 |
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doaj-f9038853bb3143b48b29ae654a722cc62020-11-24T21:52:37ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472012-01-01201210.1155/2012/376291376291A Parallel Implementation of Unscheduled Flow Control in Interconnected Power SystemsG. Ozdemir Dag0Mustafa Bagriyanik1Department of Computational Science and Engineering, Informatics Institute, Istanbul Technical University, Maslak, 34469 Istanbul, TurkeyDepartment of Electrical Engineering, Electrical & Electronics Faculty, Istanbul Technical University, Maslak, 34469 Istanbul, TurkeyThe unscheduled power flow problem needs to be minimized or controlled as soon as possible in a deregulated power system since the transmission systems are mostly operated at their power-carrying limits or very close to it. The time spent for simulations to determine the current states of all the system and control variables of the interconnected power system is important. Taking necessary action in case of any failure of equipment or any other occurrence of an undesired situation could be critical. Using supercomputing facilities and parallel computing techniques together decreases the computation time greatly. In this study, a parallel implementation of a multiobjective optimization approach based on both genetic algorithms and fuzzy decision making to manage unscheduled flows is presented. Parallel computation techniques are applied using supercomputers (high-performance computers). The proposed method is applied to the IEEE 300 bus test system. Two different cases for some parameters of GA are considered to see the power of parallel computation technique. Then the simulation results are presented.http://dx.doi.org/10.1155/2012/376291 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
G. Ozdemir Dag Mustafa Bagriyanik |
spellingShingle |
G. Ozdemir Dag Mustafa Bagriyanik A Parallel Implementation of Unscheduled Flow Control in Interconnected Power Systems Mathematical Problems in Engineering |
author_facet |
G. Ozdemir Dag Mustafa Bagriyanik |
author_sort |
G. Ozdemir Dag |
title |
A Parallel Implementation of Unscheduled Flow Control in Interconnected Power Systems |
title_short |
A Parallel Implementation of Unscheduled Flow Control in Interconnected Power Systems |
title_full |
A Parallel Implementation of Unscheduled Flow Control in Interconnected Power Systems |
title_fullStr |
A Parallel Implementation of Unscheduled Flow Control in Interconnected Power Systems |
title_full_unstemmed |
A Parallel Implementation of Unscheduled Flow Control in Interconnected Power Systems |
title_sort |
parallel implementation of unscheduled flow control in interconnected power systems |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2012-01-01 |
description |
The unscheduled power flow problem needs to be minimized or controlled as soon as possible in a deregulated power system since the transmission systems are mostly operated at their power-carrying limits or very close to it. The time spent for simulations to determine the current states of all the system and control variables of the interconnected power system is important. Taking necessary action in case of any failure of equipment or any other occurrence of an undesired situation could be critical. Using supercomputing facilities and parallel computing techniques together decreases the computation time greatly. In this study, a parallel implementation of a multiobjective optimization approach based on both genetic algorithms and fuzzy decision making to manage unscheduled flows is presented. Parallel computation techniques are applied using supercomputers (high-performance computers). The proposed method is applied to the IEEE 300 bus test system. Two different cases for some parameters of GA are considered to see the power of parallel computation technique. Then the simulation results are presented. |
url |
http://dx.doi.org/10.1155/2012/376291 |
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