HYBRIDIZATION OF ANT COLONY ALGORITHM AND PARTICLE SWARM OPTIMIZATION ALGORITHM FOR REDUCTION OF REAL POWER LOSS

Authors

  • Dr K. Lenin Professor, Department of EEE, Prasad V.Potluri Siddhartha Institute of Technology, Kanuru, Vijayawada, Andhra Pradesh -520007, India

DOI:

https://doi.org/10.29121/granthaalayah.v6.i12.2018.1092

Keywords:

Swarm Intelligence, Optimal Reactive Power, Transmission Loss

Abstract [English]

In this work Ant colony optimization algorithm (ACO) & particle swarm optimization (PSO) algorithm has been hybridized (called as APA) to solve the optimal reactive power problem. In this algorithm, initial optimization is achieved by particle swarm optimization algorithm and then the optimization process is carry out by ACO around the best solution found by PSO to finely explore the design space. In order to evaluate the proposed APA, it has been tested on IEEE 300 bus system and compared to other standard algorithms. Simulations results show that proposed APA algorithm performs well in reducing the real power loss.

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References

K. Y. Lee, “Fuel-cost minimisation for both real and reactive-power dispatches,” Proceedings Generation, Transmission and Distribution Conference, vol/issue: 131(3), pp. 85-93, 1984. DOI: https://doi.org/10.1049/ip-c.1984.0012

N. I. Deeb, “An efficient technique for reactive power dispatch using a revised linear programming approach,” Electric Power System Research, vol/issue: 15(2), pp. 121–134, 1988. DOI: https://doi.org/10.1016/0378-7796(88)90016-8

M. R. Bjelogrlic, M. S. Calovic, B. S. Babic, et. al.,” Application of Newton’s optimal power flow in voltage/reactive power control”, IEEE Trans Power System, vol. 5, no. 4, pp. 1447-1454, 1990.

S. Granville, “Optimal reactive dispatch through interior point methods,” IEEE Transactions on Power System, vol/issue: 9(1), pp. 136–146, 1994. DOI: https://doi.org/10.1109/59.317548

N. Grudinin, “Reactive power optimization using successive quadratic programming method,” IEEE Transactions on Power System, vol/issue: 13(4), pp. 1219–1225, 1998.

Wei Yan, J. Yu, D. C. Yu and K. Bhattarai,” A new optimal reactive power flow model in rectangular form and its solution by predictor corrector primal dual interior point method”, IEEE Trans. Pwr. Syst., vol.21, no.1, pp.61-67, 2006. DOI: https://doi.org/10.1109/TPWRS.2005.861978

Aparajita Mukherjee, Vivekananda Mukherjee, “Solution of optimal reactive power dispatch by chaotic krill herd algorithm", IET Gener. Transm. Distrib, Vol. 9, Issue. 15, pp. 2351–2362, 2015.

Hu, Z., Wang, X. & Taylor, G. Stochastic optimal reactive power dispatch: Formulation and solution method. Electr. Power Energy Syst., vol. 32, pp. 615-621. 2010. DOI: https://doi.org/10.1016/j.ijepes.2009.11.018

Mahaletchumi A/P Morgan, Nor Rul Hasma Abdullah, Mohd Herwan Sulaiman, Mahfuzah Mustafa and Rosdiyana Samad, “Computational intelligence technique for static VAR compensator (SVC) installation considering multi-contingencies (N-m)”, ARPN Journal of Engineering and Applied Sciences, VOL. 10, NO. 22, DECEMBER 2015.

Mohd Herwan Sulaiman, Zuriani Mustaffa, Hamdan Daniyal, Mohd Rusllim Mohamed and Omar Aliman, “Solving Optimal Reactive Power Planning Problem Utilizing Nature Inspired Computing Techniques”, ARPN Journal of Engineering and Applied Sciences, VOL. 10, NO. 21, pp.9779-9785. NOVEMBER 2015

Mohd Herwan Sulaiman, Wong Lo Ing, Zuriani Mustaffa and Mohd Rusllim Mohamed, “Grey Wolf Optimizer for Solving Economic Dispatch Problem with Valve-Loading Effects”, ARPN Journal of Engineering and Applied Sciences, VOL. 10, NO. 21, pp. 9796-9801, NOVEMBER 2015.

Pandiarajan, K. & Babulal, C. K., “Fuzzy harmony search algorithm based optimal power flow for power system security enhancement”. International Journal Electric Power Energy Syst., vol. 78, pp. 72-79. 2016. DOI: https://doi.org/10.1016/j.ijepes.2015.11.053

Mustaffa, Z., Sulaiman, M.H., Yusof, Y., Kamarulzaman, S.F., “A novel hybrid metaheuristic algorithm for short term load forecasting”, International Journal of Simulation: Systems, Science and Technology, Volume 17, Issue 41, Pages 6.1-6.6. 2017.

Sulaiman, M.H., Mustaffa, Z., Mohamed, M.R., Aliman, O., “An application of multi-verse optimizer for optimal reactive power dispatch problems”, International Journal of Simulation: Systems, Science and Technology, Volume 17, Issue 41, Pages 5.1-5.5. 2017.

Mahaletchumi A/P Morgan, Nor Rul Hasma Abdullah, Mohd Herwan Sulaiman,Mahfuzah Mustafa and Rosdiyana Samad, “Multi-Objective Evolutionary Programming (MOEP) Using Mutation Based on Adaptive Mutation Operator (AMO) Applied For Optimal Reactive Power Dispatch”, ARPN Journal of Engineering and Applied Sciences, VOL. 11, NO. 14, JULY 2016.

Rebecca Ng Shin Mei, Mohd Herwan Sulaiman, Zuriani Mustaffa, “Ant Lion Optimizer for Optimal Reactive Power Dispatch Solution”, Journal of Electrical Systems, "Special Issue AMPE2015", pp. 68-74.2016.

Mahaletchumi Morgan, Nor Rul Hasma Abdullah, Mohd Herwan Sulaiman, Mahfuzah Mustafa, Rosdiyana Samad, “Benchmark Studies on Optimal Reactive Power Dispatch (ORPD) Based Multi-objective Evolutionary Programming (MOEP) Using Mutation Based on Adaptive Mutation Adapter (AMO) and Polynomial Mutation Operator (PMO)”, Journal of Electrical Systems, 12-1, 2016.

Rebecca Ng Shin Mei, Mohd Herwan Sulaiman, Zuriani Mustaffa, Hamdan Daniyal, “Optimal Reactive Power Dispatch Solution by Loss Minimization using Moth-Flame Optimization Technique”, Applied Soft Computing, Volume 59, October, Pages 210-222, 2017. DOI: https://doi.org/10.1016/j.asoc.2017.05.057

Kaveh A, Talatahari S. A hybrid particle swarm and ant colony optimization for design of truss structure, Asian Journal of Civil Engineering, 9(2008) 329-48.

Camp CV, Bichon BJ. Design of space trusses using ant colony optimization, Journal of Structural Engineering, 130(2004) 741–51. DOI: https://doi.org/10.1061/(ASCE)0733-9445(2004)130:5(741)

Camp CV, Bichon BJ, Stovall SP. Design of steel frames using ant colony optimization, Journal of Structural Engineering, 131(2005) 369–79. DOI: https://doi.org/10.1061/(ASCE)0733-9445(2005)131:3(369)

Eberhart R, Shi Y. Engineering optimization with particle swarm. In: IEEE swarm intelligence symposium, Indianapolis, 2003, pp. 53–57.

Hassan R, Cohanim B, de Weck O, Venter G. A comparison of particle swarm optimization and the genetic algorithm. In: 1st AIAA Multidisciplinary Design Optimization Specialist Conference. No. AIAA-2005-1897. DOI: https://doi.org/10.2514/6.2005-1897

Angeline P. Evolutionary optimization versus particle swarm optimization: philosophy and performance difference, Proceeding of the Evolutionary Programming Conference, San Diego, USA, 1998. DOI: https://doi.org/10.1007/BFb0040811

Shelokar PS, Siarry P, Jayaraman VK, Kulkarni BD. Particle swarm and ant colony algorithms hybridized for improved continuous optimization, Applied Mathematics and Computation, 188(2007) 129-42. DOI: https://doi.org/10.1016/j.amc.2006.09.098

Vander plaats GN. Numerical optimization techniques for engineering design: with application. 2nd ed. New York: McGraw-Hill, 1984.

Dorigo M. Optimization, learning and natural algorithms (in Italian), PhD Thesis. Dipartimento di Elettronica, Politecnico di Milano, IT, 1992.

Dorigo M, Caro DG, Gambardella LM. Ant algorithms for discrete optimization, Art if Life, 5(1999) 137-72. DOI: https://doi.org/10.1162/106454699568728

Eberhart RC, Kennedy J. A new optimizer using particle swarm theory. In: Proceedings of the sixth international symposium on micro machine and human science, Nagoya, Japan, 1995.

Li LI, Huang ZB, Liu F, Wu QH. A heuristic particle swarm optimizer for optimization of pin connected structures, Computers and Structures, 85(1997) 340-9. DOI: https://doi.org/10.1016/j.compstruc.2006.11.020

Gholizadeh S. Optimum Design of Structures by an Improved Particle Swarm Algorithm, Asian Journal of Civil Engineering, 11(2010) 777-93.

S. Surender Reddy, “Optimal Reactive Power Scheduling Using Cuckoo Search Algorithm”, International Journal of Electrical and Computer Engineering, Vol. 7, No. 5, pp. 2349-2356. 2017 DOI: https://doi.org/10.11591/ijece.v7i5.pp2349-2356

S.S. Reddy, et al., “Faster evolutionary algorithm based optimal power flow using incremental variables”, Electrical Power and Energy Systems, vol. 54, pp. 198-210, 2014. DOI: https://doi.org/10.1016/j.ijepes.2013.07.019

IEEE, “IEEE 118, 300 -test systems”, (1993), http://www.ee.washington.edu/trsearch/pstca/.

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Published

2018-12-31

How to Cite

Lenin, K. (2018). HYBRIDIZATION OF ANT COLONY ALGORITHM AND PARTICLE SWARM OPTIMIZATION ALGORITHM FOR REDUCTION OF REAL POWER LOSS. International Journal of Research -GRANTHAALAYAH, 6(12), 121–127. https://doi.org/10.29121/granthaalayah.v6.i12.2018.1092

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