Adaptive Bacterial Foraging Oriented Particle Swarm Optimization Algorithm for Solving Optimal Reactive Power Dispatch Problem

K. Lenin; B. Ravindranath Reddy; M. Surya Kalavathi

doi:doi:10.11648/j.ijepe.20140301.11

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Adaptive Bacterial Foraging Oriented Particle Swarm Optimization Algorithm for Solving Optimal Reactive Power Dispatch Problem

K. Lenin, B. Ravindranath Reddy, M. Surya Kalavathi

Published in International Journal of Energy and Power Engineering (Volume 3, Issue 1)

Received: 13 December 2013 Accepted: Published: 20 January 2014

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Abstract

This paper presents an algorithm for solving the multi-objective reactive power dispatch problem in a power system. Modal analysis of the system is used for static voltage stability assessment. Loss minimization and maximization of voltage stability margin are taken as the objectives. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. Evolutionary algorithm and Swarm Intelligence algorithm (EA, SI), a part of Bio inspired optimization algorithm, have been widely used to solve numerous optimization problem in various science and engineering domains. Bacterial Foraging Optimization Algorithm (BFOA) has recently emerged as a very powerful technique for real parameter optimization. In order to overcome the delay in optimization and to further enhance the performance of BFO, this paper proposed a new hybrid algorithm combining the features of BFOA and Particle Swarm Optimization (PSO) called Adaptive bacterial foraging oriented particle swarm optimization (ABF-PSO) for solving reactive power dispatch problem .The simulation results demonstrate good performance of the ABF-PSO in solving an optimal reactive power dispatch problem. In order to evaluate the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms reported those before in literature. Results show that (ABF-PSO) is more efficient than others for solution of single-objective ORPD problem.

Published in	International Journal of Energy and Power Engineering (Volume 3, Issue 1)
DOI	10.11648/j.ijepe.20140301.11
Page(s)	1-6
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Bacterial Foraging Optimization Algorithm, Particle Swarm Optimization, Optimal Reactive Power, Transmission Loss

References

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[9]	D. Devaraj, and B. Yeganarayana, "Genetic algorithm based optimal power flow for security enhancement", IEE proc-Generation.Transmission and. Distribution; 152, 6 November 2005.
[10]	C.A. Canizares , A.C.Z.de Souza and V.H. Quintana , " Comparison of performance indices for detection of proximity to voltage collapse ,’’ vol. 11. no.3 , pp.1441-1450, Aug 1996 .
[11]	Passino, K.M., 2002. Bio mimicry of bacterial foraging for distributed optimization and control. IEEE Control Systems Magazine, pp. 52-67.
[12]	Karoni,W., 2008. Bacterial foraging oriented by particle swarm optimization strategy for PID tuning. In GECCO 2008: Proceedings of the Genetic and Evolutionary computation conf, pp. 1823-1826, ACM.
[13]	Dasgupta, S., Das, S., Abraham, A., Biswas, A., 2009. Adaptive Computational Chemotaxis in Bacterial Forgaing Optimization: An Analysis. IEEE Trans on Evolutionary Comp., vol. 13, pp. 919-941.
[14]	Wu Q H, Ma J T. Power system optimal reactive power dispatch using evolutionary programming. IEEE Transactions on power systems 1995; 10(3): 1243-1248 .
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[16]	D.Devaraj,’ Improved genetic algorithm for multi – objective reactive power dispatch problem’ European Transactions on electrical power 2007 ; 17: 569-581.
[17]	P. Aruna Jeyanthy and Dr. D. Devaraj "Optimal Reactive Power Dispatch for Voltage Stability Enhancement Using Real Coded Genetic Algorithm" International Journal of Computer and Electrical Engineering, Vol. 2, No. 4, August, 2010 1793-8163.

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APA Style

K. Lenin, B. Ravindranath Reddy, M. Surya Kalavathi. (2014). Adaptive Bacterial Foraging Oriented Particle Swarm Optimization Algorithm for Solving Optimal Reactive Power Dispatch Problem. International Journal of Energy and Power Engineering, 3(1), 1-6. https://doi.org/10.11648/j.ijepe.20140301.11

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ACS Style

K. Lenin; B. Ravindranath Reddy; M. Surya Kalavathi. Adaptive Bacterial Foraging Oriented Particle Swarm Optimization Algorithm for Solving Optimal Reactive Power Dispatch Problem. Int. J. Energy Power Eng. 2014, 3(1), 1-6. doi: 10.11648/j.ijepe.20140301.11

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AMA Style

K. Lenin, B. Ravindranath Reddy, M. Surya Kalavathi. Adaptive Bacterial Foraging Oriented Particle Swarm Optimization Algorithm for Solving Optimal Reactive Power Dispatch Problem. Int J Energy Power Eng. 2014;3(1):1-6. doi: 10.11648/j.ijepe.20140301.11

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@article{10.11648/j.ijepe.20140301.11,
  author = {K. Lenin and B. Ravindranath Reddy and M. Surya Kalavathi},
  title = {Adaptive Bacterial Foraging Oriented Particle Swarm Optimization Algorithm for Solving Optimal Reactive Power Dispatch Problem},
  journal = {International Journal of Energy and Power Engineering},
  volume = {3},
  number = {1},
  pages = {1-6},
  doi = {10.11648/j.ijepe.20140301.11},
  url = {https://doi.org/10.11648/j.ijepe.20140301.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijepe.20140301.11},
  abstract = {This paper presents an algorithm for solving the multi-objective reactive power dispatch problem in a power system. Modal analysis of the system is used for static voltage stability assessment. Loss minimization and maximization of voltage stability margin are taken as the objectives. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. Evolutionary algorithm and Swarm Intelligence algorithm (EA, SI), a part of Bio inspired optimization algorithm, have been widely used to solve numerous optimization problem in various science and engineering domains. Bacterial Foraging Optimization Algorithm (BFOA) has recently emerged as a very powerful technique for real parameter optimization. In order to overcome the delay in optimization and to further enhance the performance of BFO, this paper proposed a new hybrid algorithm combining the features of BFOA and Particle Swarm Optimization (PSO) called Adaptive bacterial foraging oriented particle swarm optimization (ABF-PSO) for solving reactive power dispatch problem .The simulation results demonstrate good performance of the ABF-PSO in solving an optimal reactive power dispatch problem. In order to evaluate the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms reported those before in literature. Results show that (ABF-PSO) is more efficient than others for solution of single-objective ORPD problem.},
 year = {2014}
}

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TY - JOUR
T1 - Adaptive Bacterial Foraging Oriented Particle Swarm Optimization Algorithm for Solving Optimal Reactive Power Dispatch Problem
AU - K. Lenin
AU - B. Ravindranath Reddy
AU - M. Surya Kalavathi
Y1 - 2014/01/20
PY - 2014
N1 - https://doi.org/10.11648/j.ijepe.20140301.11
DO - 10.11648/j.ijepe.20140301.11
T2 - International Journal of Energy and Power Engineering
JF - International Journal of Energy and Power Engineering
JO - International Journal of Energy and Power Engineering
SP - 1
EP - 6
PB - Science Publishing Group
SN - 2326-960X
UR - https://doi.org/10.11648/j.ijepe.20140301.11
AB - This paper presents an algorithm for solving the multi-objective reactive power dispatch problem in a power system. Modal analysis of the system is used for static voltage stability assessment. Loss minimization and maximization of voltage stability margin are taken as the objectives. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. Evolutionary algorithm and Swarm Intelligence algorithm (EA, SI), a part of Bio inspired optimization algorithm, have been widely used to solve numerous optimization problem in various science and engineering domains. Bacterial Foraging Optimization Algorithm (BFOA) has recently emerged as a very powerful technique for real parameter optimization. In order to overcome the delay in optimization and to further enhance the performance of BFO, this paper proposed a new hybrid algorithm combining the features of BFOA and Particle Swarm Optimization (PSO) called Adaptive bacterial foraging oriented particle swarm optimization (ABF-PSO) for solving reactive power dispatch problem .The simulation results demonstrate good performance of the ABF-PSO in solving an optimal reactive power dispatch problem. In order to evaluate the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms reported those before in literature. Results show that (ABF-PSO) is more efficient than others for solution of single-objective ORPD problem.
VL - 3
IS - 1
ER -

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Author Information

K. Lenin

Research Scholar, Jawaharlal Nehru Technological University Kukatpally, Hyderabad 500 085, India
B. Ravindranath Reddy

Deputy Executive Engineer, Jawaharlal Nehru Technological University Kukatpally, Hyderabad 500 085, India
M. Surya Kalavathi

Professor of Electrical and Electronics Engineering, Jawaharlal Nehru Technological University Kukatpally, Hyderabad 500 085, India

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Plain Text BibTeX RIS

APA Style

K. Lenin, B. Ravindranath Reddy, M. Surya Kalavathi. (2014). Adaptive Bacterial Foraging Oriented Particle Swarm Optimization Algorithm for Solving Optimal Reactive Power Dispatch Problem. International Journal of Energy and Power Engineering, 3(1), 1-6. https://doi.org/10.11648/j.ijepe.20140301.11

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ACS Style

K. Lenin; B. Ravindranath Reddy; M. Surya Kalavathi. Adaptive Bacterial Foraging Oriented Particle Swarm Optimization Algorithm for Solving Optimal Reactive Power Dispatch Problem. Int. J. Energy Power Eng. 2014, 3(1), 1-6. doi: 10.11648/j.ijepe.20140301.11

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AMA Style

K. Lenin, B. Ravindranath Reddy, M. Surya Kalavathi. Adaptive Bacterial Foraging Oriented Particle Swarm Optimization Algorithm for Solving Optimal Reactive Power Dispatch Problem. Int J Energy Power Eng. 2014;3(1):1-6. doi: 10.11648/j.ijepe.20140301.11

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@article{10.11648/j.ijepe.20140301.11,
  author = {K. Lenin and B. Ravindranath Reddy and M. Surya Kalavathi},
  title = {Adaptive Bacterial Foraging Oriented Particle Swarm Optimization Algorithm for Solving Optimal Reactive Power Dispatch Problem},
  journal = {International Journal of Energy and Power Engineering},
  volume = {3},
  number = {1},
  pages = {1-6},
  doi = {10.11648/j.ijepe.20140301.11},
  url = {https://doi.org/10.11648/j.ijepe.20140301.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijepe.20140301.11},
  abstract = {This paper presents an algorithm for solving the multi-objective reactive power dispatch problem in a power system. Modal analysis of the system is used for static voltage stability assessment. Loss minimization and maximization of voltage stability margin are taken as the objectives. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. Evolutionary algorithm and Swarm Intelligence algorithm (EA, SI), a part of Bio inspired optimization algorithm, have been widely used to solve numerous optimization problem in various science and engineering domains. Bacterial Foraging Optimization Algorithm (BFOA) has recently emerged as a very powerful technique for real parameter optimization. In order to overcome the delay in optimization and to further enhance the performance of BFO, this paper proposed a new hybrid algorithm combining the features of BFOA and Particle Swarm Optimization (PSO) called Adaptive bacterial foraging oriented particle swarm optimization (ABF-PSO) for solving reactive power dispatch problem .The simulation results demonstrate good performance of the ABF-PSO in solving an optimal reactive power dispatch problem. In order to evaluate the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms reported those before in literature. Results show that (ABF-PSO) is more efficient than others for solution of single-objective ORPD problem.},
 year = {2014}
}

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