Chaotic Particle Swarm Optimization for Solving Reactive Power Optimization Problem
(1) * Omar Muhammed Neda Mail (Sunni Endowment Diwan)
(2) Alfian Ma'arif Mail (Universitas Ahmad Dahlan, Indonesia)
*corresponding author

Abstract


The losses in electrical power systems are a great problem. Multiple methods have been utilized to decrease power losses in transmission lines. The proper adjusting of reactive power resources is one way to minimize the losses in any power system. Reactive Power Optimization (RPO) problem is a nonlinear and complex optimization problem and contains equality and inequality constraints. The RPO is highly essential in the operation and control of power systems. Therefore, the study concentrates on the Optimal Load Flow calculation in solving RPO problems. The Simple Particle Swarm Optimization (PSO) often falls into the local optima solution. To prevent this limitation and speed up the convergence for the Simple PSO algorithm, this study employed an improved hybrid algorithm based on Chaotic theory with PSO, called Chaotic PSO (CPSO) algorithm. Undeniably, this merging of chaotic theory in PSO algorithm can be an efficient method to slip very easily from local optima compared to Simple PSO algorithm due to remarkable behavior and high ability of the chaos. In this study, the CPSO algorithm was utilized as an optimization tool for solving the RPO problem; the main objective in this study is to decrease the power loss and enhance the voltage profile in the power system. The presented algorithm was tested on IEEE Node-14 system. The simulation implications for this system reveal that the CPSO algorithm provides the best results. It had a high ability to minimize transmission line losses and improve the system's voltage profile compared to the Simple PSO and other approaches in the literature.

Keywords


Reactive Power Optimization (RPO); Optimal Load Flow; Simple PSO; Chaotic PSO (CPSO)

   

DOI

https://doi.org/10.31763/ijrcs.v1i4.539 		      

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References


[1] L. Kanagasabai, "FCC algorithm for power loss diminution" Journal of Engineering, vol. 8, no. 1, 2021. https://doi.org/10.21272/jes.2021.8(1).e5

[2] R. R. Shoults and D. T. Sun, “Optimal Power Flow Based Upon P-Q Decomposition,” IEEE Transactions on Power Apparatus and Systems, vol. PAS-101, no. 2, pp. 397–405, Feb. 1982. https://doi.org/10.1109/TPAS.1982.317120

[3] K. C. Mamandur and R. Chenoweth, “Optimal Control of Reactive Power flow for Improvements in Voltage Profiles and for Real Power Loss Minimization,” IEEE Transactions on Power Apparatus and Systems, vol. PAS-100, no. 7, pp. 3185–3194, Jul. 1981. https://doi.org/10.1109/TPAS.1981.316646

[4] H. Habibollahzadeh, G.-X. Luo, and A. Semlyen, “Hydrothermal optimal power flow based on a combined linear and nonlinear programming methodology,” IEEE Transactions on Power Systems, vol. 4, no. 2, pp. 530–537, May 1989. https://doi.org/10.1109/59.193826

[5] K. Aoki, A. Nishikori, and R. Yokoyama, “Constrained Load Flow Using Recursive Quadratic Programming,” IEEE Transactions on Power Systems, vol. 2, no. 1, pp. 8–16, 1987. https://doi.org/10.1109/TPWRS.1987.4335064

[6] Xihui Yan and V. H. Quintana, “Improving an interior-point-based OPF by dynamic adjustments of step sizes and tolerances,” IEEE Transactions on Power Systems, vol. 14, no. 2, pp. 709–717, May 1999. https://doi.org/10.1109/59.761902

[7] J. A. Momoh and J. Z. Zhu, “Improved interior point method for OPF problems,” IEEE Transactions on Power Systems, vol. 14, no. 3, pp. 1114–1120, 1999. https://doi.org/10.1109/59.780938

[8] D. Sun, B. Ashley, B. Brewer, A. Hughes, and W. Tinney, “Optimal Power Flow By Newton Approach,” IEEE Transactions on Power Apparatus and Systems, vol. PAS-103, no. 10, pp. 2864–2880, Oct. 1984. https://doi.org/10.1109/TPAS.1984.318284

[9] L. L. Lai, J. T. Ma, R. Yokoyama, and M. Zhao, “Improved genetic algorithms for optimal power flow under both normal and contingent operation states,” International Journal of Electrical Power & Energy Systems, vol. 19, no. 5, pp. 287–292, Jun. 1997. https://doi.org/10.1016/S0142-0615(96)00051-8

[10] S. Granville, “Optimal reactive dispatch through interior point methods,” IEEE Transactions on Power Systems, vol. 9, no. 1, pp. 136–146, 1994. https://doi.org/10.1109/59.317548

[11] R. Hooshmand and M. Joorabian, “Application of artificial neural networks in controlling voltage and reactive power,” Scientia Iranica, vol. 12, no. 1, pp. 99–108, 2005. https://www.sid.ir/en/journal/ViewPaper.aspx?ID=86506

[12] D. Pudjianto, S. Ahmed, and G. Strbac, “Allocation of VAR support using LP and NLP based optimal power flows,” IEE Proc. Gen. Trans. Dist., vol. 149, no. 4, pp. 377–383, 2002. https://doi.org/10.1049/ip-gtd:20020200

[13] D. C. Yu, J. E. Fagan, B. Foote, and A. A. Aly, “An optimal load flow study by the generalized reduced gradient approach,” Electric Power Systems Research, vol. 10, no. 1, pp. 47–53, Jan. 1986. https://doi.org/10.1016/0378-7796(86)90048-9

[14] K. L. Lo and S. P. Zhu, “A decoupled quadratic programming approach for optimal power dispatch,” Electric Power Systems Research, vol. 22, no. 1, pp. 47–60, Sep. 1991. https://doi.org/10.1016/0378-7796(91)90079-3

[15] F.C. Lu, Y.Y. Hsu, Reactive power/voltage control in a distribution substation using dynamic programming, IEE Proc. Gen. Trans. Distrib., vol. 142, pp. 639–645, 1995. https://doi.org/10.1049/ip-gtd:19952210

[16] K. Iba, “Reactive power optimization by genetic algorithm,” IEEE Transactions on Power Systems, vol. 9, no. 2, pp. 685–692, May 1994. https://doi.org/10.1109/59.317674

[17] W. Yan, F. Liu, C. Y. Chung, and K. P. Wong, “A Hybrid Genetic Algorithm–Interior Point Method for Optimal Reactive Power Flow,” IEEE Transactions on Power Systems, vol. 21, no. 3, pp. 1163–1169, Aug. 2006. https://doi.org/10.1109/TPWRS.2006.879262

[18] K. H. Adbul-Rahman and S. M. Shahidehpour, “Optimal reactive power dispatch with fuzzy variables,” 1993 IEEE International Symposium on Circuits and Systems. https://doi.org/10.1109/ISCAS.1993.394193

[19] R. Ng Shin Mei, M. H. Sulaiman, Z. Mustaffa, and H. Daniyal, “Optimal reactive power dispatch solution by loss minimization using moth-flame optimization technique,” Applied Soft Computing, vol. 59, pp. 210–222, Oct. 2017. https://doi.org/10.1016/j.asoc.2017.05.057

[20] H. Yoshida, K. Kawata, Y. Fukuyama, S. Takayama, and Y. Nakanishi, “A particle swarm optimization for reactive power and voltage control considering voltage security assessment,” IEEE Transactions on Power Systems, vol. 15, no. 4, pp. 1232–1239, 2000. https://doi.org/10.1109/59.898095

[21] Mojtaba Ghasemi, Sahand Ghavidel, Mohammad Mehdi Ghanbarian, Amir Habibi, " A new hybrid algorithm for optimal reactive power dispatch problem with discrete and continuous control variables," Applied Soft Computing, Vol. 22, PP. 126-140, 2014. https://doi.org/10.1016/j.asoc.2014.05.006

[22] O. M. Neda, "A new hybrid algorithm for solving distribution network reconfiguration under different load conditions," Indonesian Journal of Electrical Engineering and Computer Science, vol. 20, no. 3, pp. 1118-1127, 2020. https://doi.org/10.11591/ijeecs.v20.i3.pp1118-1127

[23] O. M. Neda, "Optimal coordinated design of PSS and UPFC-POD using DEO algorithm to enhance damping performance," International Journal of Electrical and Computer Engineering (IJECE), vol. 10, no. 6, pp. 6111-6121, 2020. https://doi.org/10.11591/ijece.v10i6.pp6111-6121

[24] A. N. Hussain, A. A. Abdullah and O. M. Neda, "Modified particle swarm optimization for solution of reactive power dispatch," Research Journal of Applied Sciences, Engineering and Technology, vol. 15, no. 8, pp. 316-327, 2018. https://doi.org/10.19026/rjaset.15.5917

[25] A. Rajan and T. Malakar, “Optimal reactive power dispatch using hybrid Nelder–Mead simplex based firefly algorithm,” International Journal of Electrical Power & Energy Systems, vol. 66, pp. 9–24, Mar. 2015. https://doi.org/10.1016/j.ijepes.2014.10.041

[26] T. Kennedy and R. Eberhart, "Particle swarm optimization," In Proc. Of the IEEE international conference on Neural networks, 1995, pp. 1942-1948. https://doi.org/10.1109/ICNN.1995.488968

[27] M. Damdar and V. C. Veera Reddy, “Capacitor Placement Using Fuzzy And Particle Swarm Optimization Method For Maximum Annual Savings,” ARPN Journal of Engineering and Applied Sciences, vol. 3, no. 3, pp. 25–30, June 2008. https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.510.6282&rep=rep1&type=pdf

[28] R. C. Eberhart and Y. Shi, “Comparing inertia weights and constriction factors in particle swarm optimization”, In Proceedings of the 2000 Congress on Evolutionary Computation, (CEC00), July 16-19, 2000, pp. 84–88. https://doi.org/10.1109/CEC.2000.870279

[29] A. N. Hussaina, F. Malek, M. A. Rashid, L. Mohamed, and N. A. Mohd Affendi, “Optimal Coordinated Design of Multiple Damping Controllers Based on PSS and UPFC Device to Improve Dynamic Stability in the Power System,” Mathematical Problems in Engineering., vol. 2013, pp. 1–16, Feb 2013. https://doi.org/10.1155/2013/965282


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International Journal of Robotics and Control Systems
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