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Optimization of distribution network configuration for loss reduction using artificial bee colony algorithm
| Venue: | International Journal of Electrical Power and Energy Systems Engineering |
| Citations: | 13 - 0 self |
BibTeX
@ARTICLE{Rao_optimizationof,
author = {R. Srinivasa Rao and S. V. L. Narasimham and M. Ramalingaraju},
title = {Optimization of distribution network configuration for loss reduction using artificial bee colony algorithm},
journal = {International Journal of Electrical Power and Energy Systems Engineering},
year = {},
pages = {116--122}
}
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Abstract
Abstract—Network reconfiguration in distribution system is realized by changing the status of sectionalizing switches to reduce the power loss in the system. This paper presents a new method which applies an artificial bee colony algorithm (ABC) for determining the sectionalizing switch to be operated in order to solve the distribution system loss minimization problem. The ABC algorithm is a new population based metaheuristic approach inspired by intelligent foraging behavior of honeybee swarm. The advantage of ABC algorithm is that it does not require external parameters such as cross over rate and mutation rate as in case of genetic algorithm and differential evolution and it is hard to determine these parameters in prior. The other advantage is that the global search ability in the algorithm is implemented by introducing neighborhood source production mechanism which is a similar to mutation process. To demonstrate the validity of the proposed algorithm, computer simulations are carried out on 14, 33, and 119-bus systems and compared with different approaches available in the literature. The proposed method has outperformed the other methods in terms of the quality of solution and computational efficiency.
Keyphrases
artificial bee colony algorithm loss reduction distribution network configuration abc algorithm mutation rate metaheuristic approach external parameter new method global search ability different approach power loss abstract network reconfiguration mutation process new population computational efficiency genetic algorithm honeybee swarm computer simulation distribution system loss minimization problem 119-bus system neighborhood source production mechanism differential evolution distribution system
