Efficient Hybrid Algorithm Solution for Optimal Reactive Power Flow Using the Sensitive Bus Approach
Received: 11 December 2021 | Revised: 1 January 2022 | Accepted: 7 January 2022 | Online: 20 January 2022
Corresponding author: Z. Sahli
Abstract
This paper presents the design and application of an efficient hybrid algorithm for solving the Optimal Reactive Power Flow (ORPF) problem. The ORPF is formulated as a nonlinear constrained optimization problem where the active power losses must be minimized. The proposed approach is based on the hybridization of Particle Swarm Optimization (PSO) and Tabu-Search (TS) technique. The proposed PSO-TS approach is used to find the settings of the control variables (i.e. generation bus voltages, transformer taps, and shunt capacitor sizes) which minimize transmission active power losses. The bus locations of the shunt capacitors are identified according to sensitive buses. To show the effectiveness of the proposed method, it is applied to the IEEE 30 bus benchmark test system and is compared with PSO and TS without hybridization, along with some other published approaches. The obtained results reveal the effectiveness of the proposed method in dealing with the highly nonlinear constrained nature of the ORPF problem.
Keywords:
optimal reactive power flow, active power loss minimization, hybrid methods, particle swarm optimization, tabu search, sensitive busDownloads
References
B. Zhao, C. X. Guo, and Y. J. Cao, "A multiagent-based particle swarm optimization approach for optimal reactive power dispatch," IEEE Transactions on Power Systems, vol. 20, no. 2, pp. 1070–1078, Feb. 2005. DOI: https://doi.org/10.1109/TPWRS.2005.846064
H. Yapici, "Solution of optimal reactive power dispatch problem using pathfinder algorithm," Engineering Optimization, vol. 53, no. 11, pp. 1946–1963, Aug. 2021. DOI: https://doi.org/10.1080/0305215X.2020.1839443
A. Abbasy and S. H. Hosseini, "Ant Colony Optimization-Based Approach to Optimal Reactive Power Dispatch: A Comparison of Various Ant Systems," in IEEE Power Engineering Society Conference and Exposition in Africa - PowerAfrica, Johannesburg, South Africa, Jul. 2007, pp. 1–8. DOI: https://doi.org/10.1109/PESAFR.2007.4498067
B. Zhao, C. X. Guo, and Y. J. Cao, "An improved particle swarm optimization algorithm for optimal reactive power dispatch," in IEEE Power Engineering Society General Meeting, San Francisco, CA, USA, Jun. 2005, pp. 272-279 Vol. 1.
N. Deeb and S. M. Shahidehpour, "Linear reactive power optimization in a large power network using the decomposition approach," IEEE Transactions on Power Systems, vol. 5, no. 2, pp. 428–438, Feb. 1990. DOI: https://doi.org/10.1109/59.54549
K. Y. Lee, Y. M. Park, and J. L. Ortiz, "A United Approach to Optimal Real and Reactive Power Dispatch," IEEE Transactions on Power Apparatus and Systems, vol. PAS-104, no. 5, pp. 1147–1153, Feb. 1985. DOI: https://doi.org/10.1109/TPAS.1985.323466
J. S. Horton and L. L. Grigsby, "Voltage Optimization Using Combined Linear Programming amp; Gradient Techniques," IEEE Transactions on Power Apparatus and Systems, vol. PAS-103, no. 7, pp. 1637–1643, Jul. 1984. DOI: https://doi.org/10.1109/TPAS.1984.318645
S. S. Sachdeva and R. Billinton, "Optimum Network Var Planning by Nonlinear Programming," IEEE Transactions on Power Apparatus and Systems, vol. PAS-92, no. 4, pp. 1217–1225, Jul. 1973. DOI: https://doi.org/10.1109/TPAS.1973.293803
K. Mahadevan and P. S. Kannan, "Comprehensive learning particle swarm optimization for reactive power dispatch," Applied Soft Computing, vol. 10, no. 2, pp. 641–652, Nov. 2010. DOI: https://doi.org/10.1016/j.asoc.2009.08.038
V. H. Quintana and M. Santos-Nieto, "Reactive-power dispatch by successive quadratic programming," IEEE Transactions on Energy Conversion, vol. 4, no. 3, pp. 425–435, Sep. 1989. DOI: https://doi.org/10.1109/60.43245
S. Granville, "Optimal reactive dispatch through interior point methods," IEEE Transactions on Power Systems, vol. 9, no. 1, pp. 136–146, Oct. 1994. DOI: https://doi.org/10.1109/59.317548
M. A. Abido, "Optimal power flow using particle swarm optimization," International Journal of Electrical Power & Energy Systems, vol. 24, no. 7, pp. 563–571, Jul. 2002. DOI: https://doi.org/10.1016/S0142-0615(01)00067-9
W. N. W. Abdullah, H. Saibon, A. A. M. Zain, and K. L. Lo, "Genetic algorithm for optimal reactive power dispatch," in Proceedings of EMPD ’98. 1998 International Conference on Energy Management and Power Delivery (Cat. No.98EX137), Singapore, Singapore, Mar. 1998, vol. 1, pp. 160–164 vol.1.
A. A. A. E. Ela, M. A. Abido, and S. R. Spea, "Differential evolution algorithm for optimal reactive power dispatch," Electric Power Systems Research, vol. 81, no. 2, pp. 458–464, Oct. 2011. DOI: https://doi.org/10.1016/j.epsr.2010.10.005
K. Teeparthi and D. M. V. Kumar, "Dynamic Power System Security Analysis Using a Hybrid PSO-APO Algorithm," Engineering, Technology & Applied Science Research, vol. 7, no. 6, pp. 2124–2131, Dec. 2017. DOI: https://doi.org/10.48084/etasr.1477
T. L. Duong and T. T. Nguyen, "Application of Sunflower Optimization Algorithm for Solving the Security Constrained Optimal Power Flow Problem," Engineering, Technology & Applied Science Research, vol. 10, no. 3, pp. 5700–5705, Jun. 2020. DOI: https://doi.org/10.48084/etasr.3511
Q. H. Wu and J. T. Ma, "Power system optimal reactive power dispatch using evolutionary programming," IEEE Transactions on Power Systems, vol. 10, no. 3, pp. 1243–1249, Dec. 1995. DOI: https://doi.org/10.1109/59.466531
H. Pulluri, R. Naresh, and V. Sharma, "Application of stud krill herd algorithm for solution of optimal power flow problems," International Transactions on Electrical Energy Systems, vol. 27, no. 6, 2017, Art. no. e2316. DOI: https://doi.org/10.1002/etep.2316
K. ben oualid Medani, S. Sayah, and A. Bekrar, "Whale optimization algorithm based optimal reactive power dispatch: A case study of the Algerian power system," Electric Power Systems Research, vol. 163, pp. 696–705, Jul. 2018. DOI: https://doi.org/10.1016/j.epsr.2017.09.001
A. Q. H. Badar, B. S. Umre, and A. S. Junghare, "Reactive power control using dynamic Particle Swarm Optimization for real power loss minimization," International Journal of Electrical Power & Energy Systems, vol. 41, no. 1, pp. 133–136, Jul. 2012. DOI: https://doi.org/10.1016/j.ijepes.2012.03.030
U. Khaled, A. M. Eltamaly, and A. Beroual, "Optimal Power Flow Using Particle Swarm Optimization of Renewable Hybrid Distributed Generation," Energies, vol. 10, no. 7, Jul. 2017, Art. no. 1013. DOI: https://doi.org/10.3390/en10071013
B. Shaw, V. Mukherjee, and S. P. Ghoshal, "Solution of reactive power dispatch of power systems by an opposition-based gravitational search algorithm," International Journal of Electrical Power & Energy Systems, vol. 55, pp. 29–40, Oct. 2014. DOI: https://doi.org/10.1016/j.ijepes.2013.08.010
R. Thangaraj, M. Pant, A. Abraham, and P. Bouvry, "Particle swarm optimization: Hybridization perspectives and experimental illustrations," Applied Mathematics and Computation, vol. 217, no. 12, pp. 5208–5226, Oct. 2011. DOI: https://doi.org/10.1016/j.amc.2010.12.053
J. G. Vlachogiannis and K. Y. Lee, "A Comparative Study on Particle Swarm Optimization for Optimal Steady-State Performance of Power Systems," IEEE Transactions on Power Systems, vol. 21, no. 4, pp. 1718–1728, Aug. 2006. DOI: https://doi.org/10.1109/TPWRS.2006.883687
P. K. Roy, S. P. Ghoshal, and S. S. Thakur, "Optimal VAR control for improvements in voltage profiles and for real power loss minimization using Biogeography Based Optimization," International Journal of Electrical Power & Energy Systems, vol. 43, no. 1, pp. 830–838, Sep. 2012. DOI: https://doi.org/10.1016/j.ijepes.2012.05.032
R. Mallipeddi, S. Jeyadevi, P. N. Suganthan, and S. Baskar, "Efficient constraint handling for optimal reactive power dispatch problems," Swarm and Evolutionary Computation, vol. 5, pp. 28–36, May 2012. DOI: https://doi.org/10.1016/j.swevo.2012.03.001
J. Chuanwen and E. Bompard, "A hybrid method of chaotic particle swarm optimization and linear interior for reactive power optimisation," Mathematics and Computers in Simulation, vol. 68, no. 1, pp. 57–65, Oct. 2005. DOI: https://doi.org/10.1016/j.matcom.2004.10.003
B. Bhattacharyya, S. K. Goswami, and R. C. Bansal, "Hybrid fuzzy particle swarm optimization approach for reactive power optimization," Journal of Electrical Systems, vol. 5, no. 3, pp. 1–15, 2009.
E. Naderi, H. Narimani, M. Fathi, and M. R. Narimani, "A novel fuzzy adaptive configuration of particle swarm optimization to solve large-scale optimal reactive power dispatch," Applied Soft Computing, vol. 53, pp. 441–456, Dec. 2017. DOI: https://doi.org/10.1016/j.asoc.2017.01.012
Y. Li et al., "Optimal Reactive Power Dispatch Using Particle Swarms Optimization Algorithm Based Pareto Optimal Set," in 6th International Symposium on Neural Networks, Wuhan, China, May 2009, pp. 152–161. DOI: https://doi.org/10.1007/978-3-642-01513-7_17
M. A. M. Shaheen, H. M. Hasanien, and A. Alkuhayli, "A novel hybrid GWO-PSO optimization technique for optimal reactive power dispatch problem solution," Ain Shams Engineering Journal, vol. 12, no. 1, pp. 621–630, Nov. 2021. DOI: https://doi.org/10.1016/j.asej.2020.07.011
S. Sayah and A. Hamouda, "A hybrid differential evolution algorithm based on particle swarm optimization for nonconvex economic dispatch problems," Applied Soft Computing, vol. 13, no. 4, pp. 1608–1619, Dec. 2013. DOI: https://doi.org/10.1016/j.asoc.2012.12.014
M. Mehdinejad, B. Mohammadi-Ivatloo, R. Dadashzadeh-Bonab, and K. Zare, "Solution of optimal reactive power dispatch of power systems using hybrid particle swarm optimization and imperialist competitive algorithms," International Journal of Electrical Power & Energy Systems, vol. 83, pp. 104–116, Sep. 2016. DOI: https://doi.org/10.1016/j.ijepes.2016.03.039
K. Lenin, B. R. Reddy, and M. S. Kalavathi, "Hybrid Genetic Algorithm and Particle Swarm Optimization (HGAPSO) Algorithm for Solving Optimal Reactive Power Dispatch Problem," International Journal of Electronics and Electrical Engineering, vol. 1, no. 4, pp. 262–268, 2013. DOI: https://doi.org/10.12720/ijeee.1.4.262-268
S. Mugemanyi, Z. Qu, F. X. Rugema, Y. Dong, C. Bananeza, and L. Wang, "Optimal Reactive Power Dispatch Using Chaotic Bat Algorithm," IEEE Access, vol. 8, pp. 65830–65867, 2020.
S. Mugemanyi, Z. Qu, F. X. Rugema, Y. Dong, C. Bananeza, and L. Wang, "Optimal Reactive Power Dispatch Using Chaotic Bat Algorithm," IEEE Access, vol. 8, pp. 65830–65867, 2020. DOI: https://doi.org/10.1109/ACCESS.2020.2982988
Z. M. Zohrabad, "Application of Hybrid HS and Tabu Search Algorithm for Optimal Location of FACTS Devices to Reduce Power Losses in Power Systems," Engineering, Technology & Applied Science Research, vol. 6, no. 6, pp. 1217–1220, Dec. 2016. DOI: https://doi.org/10.48084/etasr.725
R. Eberhart and J. Kennedy, "A new optimizer using particle swarm theory," in Sixth International Symposium on Micro Machine and Human Science, Nagoya, Japan, Oct. 1995, pp. 39–43.
X. Hu and R. Eberhart, "Solving Constrained Nonlinear Optimization Problems with Particle Swarm Optimization," in 6th World Multiconference on Systemics, Cybernetics and Informatics, Orlando, FL, USA, Jul. 2002, pp. 203–206.
F. Glover and M. Laguna, "Tabu Search," in Handbook of Combinatorial Optimization, D.-Z. Du and P. M. Pardalos, Eds. Boston, MA, USA: Springer, 1998, pp. 2093–2229. DOI: https://doi.org/10.1007/978-1-4613-0303-9_33
R. Chelouah and P. Siarry, "Enhanced Continuous Tabu Search: An Algorithm for Optimizing Multiminima Functions," in Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimization, Boston, MA, USA: Springer, 1999, pp. 49–61. DOI: https://doi.org/10.1007/978-1-4615-5775-3_4
Downloads
How to Cite
License
Copyright (c) 2022 Z. Sahli, A. Hamouda, S. Sayah, D. Trentesaux, A. Bekrar
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain the copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after its publication in ETASR with an acknowledgement of its initial publication in this journal.
