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Congestion management using adaptive bacterial foraging algorithm
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DOI：10.1016/j.enconman.2009.01.029.png)
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Abstract
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The economical operation of power system is associated with many sub-problems. The electric market background makes the operation of system further complicated one. The congestion management problem can be devised as the emerging problem needs to concentrate much in order to supply power to the consumers in most reliable manner. In this paper we have tried to remove the congestion in the transmission line by generation rescheduling with the cost involved in the rescheduling process should be minimized. The adaptive bacterial foraging algorithm with Nelder-Mead (ABFNM) is used in this work to optimize the congestion cost. The results are also compared with the genetic algorithm (CA), particle swarm optimization (PSO) and simple bacterial foraging (SBF) algorithms. Numerical results for the standard IEEE 30 bus system having six generating units have been presented to demonstrate the performance of the algorithm. (C) 2009 Elsevier Ltd. All rights reserved.
Keywords:
Bacterial foraging
Congestion management
Wheeling transactions
Optimal power flow
Nelder-Mead algorithm
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