Optimum Reactive Power Dispatch Solution using Hybrid Particle Swarm Optimization and Pathfinder Algorithm
Keywords:optimum reactive power dispatch HPSO-PFA, pathfinder algorithm (PFA), minimization of power loss
Optimum reactive power dispatch (ORPD) significantly impacts the operation and control of electrical power systems (EPS) due to its undeniable benefit in the economic operation and reliability of the systems. ORPD is a sub-problem of optimal power flow (OPF). The main aim is to reduce/minimize the real power loss. Among the swarm intelligence (SI) metaheuristic algorithms is particle swarm optimization (PSO), which has fast convergence speed and gives the optimum solution to a particular problem by moving the swarm in the intensification (exploitation) search space. Also, the pathfinder algorithm (PFA) mimics the collective movement of the swarms with a leading member. Therefore, combining the fast convergence of PSO with PFA to form a hybrid technique is considered a viable approach in this study to avoid decreasing PFA searchability when the dimension of the problem increases. In this article, a hybrid algorithm based on a particle swarm optimization and pathfinder algorithm (HPSO-PFA) is proposed for the first time to study the combination of the control variables (generator voltage, transformer tap, and sizing of reactive compensation to obtain the objective function (total real power loss). The proposed method is tested on the IEEE 30 and 118 bus systems. The losses were reduced to 16.14262 MW and 107.2913 MW for the IEEE 30 and 118 test systems. Furthermore, the percentage (%) reduction for the IEEE 30 and 118 test systems are 9.8% and 19.25%, respectively. The result demonstrates the performance of HPSO-PFA gives a better solution than the other algorithms.
B. Zhao, C. X. Guo and Y. J. Cao, “A multiagent-based particle swarm optimization approach for optimal reactive power dispatch,” IEEE Trans. POWER Syst., vol. 20, no. 2, pp. 1070–1078, 2005. https://doi.org/10.1109/TPWRS.2005.846064.
M. H. Sulaiman, Z. Mustaffa, M. R. Mohamed, and O. Aliman, “Using the gray wolf optimizer for solving optimal reactive power dispatch problem,” Appl. Soft Comput. J., vol. 32, pp. 286–292, 2015. https://doi.org/10.1016/j.asoc.2015.03.041.
A. H. Khazali and M. Kalantar, “Optimal reactive power dispatch based on harmony search algorithm,” Int. J. Electr. Power Energy Syst., vol. 33, no. 3, pp. 684–692, 2011. https://doi.org/10.1016/j.ijepes.2010.11.018.
M. Ghasemi, S. Ghavidel, M. M. Ghanbarian, and A. Habibi, “A new hybrid algorithm for optimal reactive power dispatch problem with discrete and continuous control variables,” Appl. Soft Comput. J., vol. 22, pp. 126–140, 2014. https://doi.org/10.1016/j.asoc.2014.05.006.
A. Ghasemi, K. Valipour, and A. Tohidi, “Multi objective optimal reactive power dispatch using a new multi objective strategy,” Int. J. Electr. Power Energy Syst., vol. 57, pp. 318–334, 2014. https://doi.org/10.1016/j.ijepes.2013.11.049.
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,” Appl. Soft Comput. J., vol. 59, pp. 210–222, 2017. https://doi.org/10.1016/j.asoc.2017.05.057.
S. Granville, “Opiimal reactive dispatch through interior point methods,” IEEE Trans. Power Syst., vol. 9, no. 1, pp. 136–146, 1994. https://doi.org/10.1109/59.317548.
K. L. Lo and S. P. Zhu, “A decoupled quadratic programming approach for optimal power dispatch,” Electr. Power Syst. Res., vol. 22, no. 1, pp. 47–60, 1991. https://doi.org/10.1016/0378-7796(91)90079-3.
N. I. Deeb and S. M. Shahidehpour, “An efficient technique for reactive power dispatch using a revised linear programming approach,” Electr. Power Syst. Res., vol. 15, no. 2, pp. 121–134, 1988. https://doi.org/10.1016/0378-7796(88)90016-8.
K. Aoki, M. Fan, and A. Nishikori, “Optimal var planning by approximation method for recursive mixed-integer linear programming,” IEEE Trans. Power Syst., vol. 3, no. 4, pp. 1741–1747, 1988. https://doi.org/10.1109/59.192990.
M. R. AlRashidi and M. E. El-Hawary, “Applications of computational intelligence techniques for solving the revived optimal power flow problem,” Electr. Power Syst. Res., vol. 79, no. 4, pp. 694–702, 2009. https://doi.org/10.1016/j.epsr.2008.10.004.
J. G. Vlachogiannis and K. Y. Lee, “A comparative study on particle swarm optimization for optimal steady-state performance of power systems,” IEEE Trans. Power Syst., vol. 21, no. 4, pp. 1718–1728, 2006. https://doi.org/10.1109/TPWRS.2006.883687.
C. Bingane, M. F. Anjos, and S. Le Digabel, “Tight-and-cheap conic relaxation for the optimal reactive power dispatch problem,” IEEE Trans. Power Syst., vol. 34, no. 6, pp. 4684–4693, 2019. https://doi.org/10.1109/TPWRS.2019.2912889.
E. Davoodi, E. Babaei, B. Mohammadi-Ivatloo, and M. Rasouli, “A novel fast semidefinite programming-based approach for optimal reactive power dispatch,” IEEE Trans. Ind. Informatics, vol. 16, no. 1, pp. 288–298, 2020. https://doi.org/10.1109/TII.2019.2918143.
A. F. Barakat, R. A. El-Sehiemy, M. I. Elsayd, and E. Osman, “An enhanced jaya optimization algorithm (EJOA) for solving multi-objective ORPD problem,” Proc. 2019 Int. Conf. Innov. Trends Comput. Eng. ITCE 2019, no. February, pp. 479–484, 2019. https://doi.org/10.1109/ITCE.2019.8646363.
T. T. Nguyen, D. N. Vo, H. Van Tran, and L. Van Dai, “Optimal dispatch of reactive power using modified stochastic fractal search algorithm,” Complexity, vol. 2019, 2019. https://doi.org/10.1155/2019/4670820.
T. T. Nguyen and D. N. Vo, “Improved social spider optimization algorithm for optimal reactive power dispatch problem with different objectives,” Neural Computing and Applications, vol. 32, no. 10, pp. 5919-5950, 2020. https://doi.org/10.1007/s00521-019-04073-4.
Z. Li, Y. Cao, L. Van Dai, X. Yang, and T. T. Nguyen, “Finding solutions for optimal reactive power dispatch problem by a novel improved antlion optimization algorithm,” Energies, vol. 12, no. 15, 2019. https://doi.org/10.3390/en12152968.
S. Abdel-Fatah, M. Ebeed, and S. Kamel, “Optimal reactive power dispatch using modified sine cosine algorithm,” Proceedings of the 2019 Int. Conf. Innov. Trends Comput. Eng. ITCE 2019, no. February, pp. 510–514, 2019. https://doi.org/10.1109/ITCE.2019.8646460.
P. P. Biswas, P. N. Suganthan, R. Mallipeddi, and G. A. J. Amaratunga, “Optimal reactive power dispatch with uncertainties in load demand and renewable energy sources adopting scenario-based approach,” Appl. Soft Comput. J., vol. 75, pp. 616–632, 2019..
M. Ş. Üney and N. Çetinkaya, “New metaheuristic algorithms for reactive power optimization,” Teh. Vjesn., vol. 26, no. 5, pp. 1427–1433, 2019. https://doi.org/10.17559/TV-20181205153116.
T. Das et al., Optimal reactive power dispatch incorporating solar power using Jaya algorithm, vol. 575. Springer Singapore, 2020. https://doi.org/10.1007/978-981-13-8687-9_4.
A. F. Barakat, R. A. El-Sehiemy, M. I. Elsayd, and E. Osman, “Solving reactive power dispatch problem by using JAYA optimization algorithm,” Int. J. Eng. Res. Africa, vol. 36, pp. 12–24, 2018. https://doi.org/10.4028/www.scientific.net/JERA.36.12.
A. M. Shaheen, R. A. El-Sehiemy, and S. M. Farrag, “Integrated strategies of backtracking search optimizer for solving reactive power dispatch problem,” IEEE Syst. J., vol. 12, no. 1, pp. 424–433, 2018. https://doi.org/10.1109/JSYST.2016.2573799.
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,” Electr. Power Syst. Res., vol. 163, pp. 696–705, 2018. https://doi.org/10.1016/j.epsr.2017.09.001.
A. A. Heidari, R. Ali Abbaspour, and A. Rezaee Jordehi, “Gaussian bare-bones water cycle algorithm for optimal reactive power dispatch in electrical power systems,” Appl. Soft Comput. J., vol. 57, pp. 657–671, 2017. https://doi.org/10.1016/j.asoc.2017.04.048.
S. Mouassa, T. Bouktir, and A. Salhi, “Ant lion optimizer for solving optimal reactive power dispatch problem in power systems,” Eng. Sci. Technol. an Int. J., vol. 20, no. 3, pp. 885–895, 2017. https://doi.org/10.1016/j.jestch.2017.03.006.
A. Mukherjee and V. Mukherjee, “Chaotic krill herd algorithm for optimal reactive power dispatch considering FACTS devices,” Appl. Soft Comput. J., vol. 44, pp. 163–190, 2016. https://doi.org/10.1016/j.asoc.2016.03.008.
R. P. Singh, V. Mukherjee, and S. P. Ghoshal, “Optimal reactive power dispatch by particle swarm optimization with an aging leader and challengers,” Appl. Soft Comput. J., vol. 29, pp. 298–309, 2015. https://doi.org/10.1016/j.asoc.2015.01.006.
M. Ghasemi, M. M. Ghanbarian, S. Ghavidel, S. Rahmani, and E. Mahboubi Moghaddam, “Modified teaching learning algorithm and double differential evolution algorithm for optimal reactive power dispatch problem: A comparative study,” Inf. Sci. (Ny)., vol. 278, pp. 231–249, 2014. https://doi.org/10.1016/j.ins.2014.03.050.
L. Le Dinh, D. Vo Ngoc, and P. Vasant, “Artificial bee colony algorithm for solving optimal power flow problem,” Sci. World J., vol. 2013, 2013. https://doi.org/10.1155/2013/159040.
S. Duman, U. Güvenç, Y. Sönmez, and N. Yörükeren, “Optimal power flow using gravitational search algorithm,” Energy Convers. Manag., vol. 59, pp. 86–95, 2012. https://doi.org/10.1016/j.enconman.2012.02.024.
Z. Zandi, E. Afjei, and M. Sedighizadeh, “Reactive power dispatch using Big Bang-Big Crunch optimization algorithm for voltage stability enhancement,” PECon 2012 – 2012 IEEE Int. Conf. Power Energy, no. December, pp. 239–244, 2012. https://doi.org/10.1109/PECon.2012.6450215.
K. Mahadevan and P. S. Kannan, “Comprehensive learning particle swarm optimization for reactive power dispatch,” Appl. Soft Comput. J., vol. 10, no. 2, pp. 641–652, 2010. https://doi.org/10.1016/j.asoc.2009.08.038.
S. Oladipo, Y. Sun, and Z. Wang, “Application of a new fusion of flower pollinated with pathfinder algorithm for AGC of multi-source interconnected power system,” IEEE Access, vol. 9, pp. 94149–94168, 2021. https://doi.org/10.1109/ACCESS.2021.3093084.
V. Suresh and S. Senthil Kumar, “Research on hybrid modified pathfinder algorithm for optimal reactive power dispatch,” Bull. Polish Acad. Sci. Tech. Sci., vol. 69, no. 4, pp. 1–8, 2021. https://doi.org/10.24425/bpasts.2021.137733.
S. Oladipo, Y. Sun, and Z. Wang, “An enhanced flower pollinated algorithm with a modified fluctuation rate for global optimisation and load frequency control system,” IET Renew. Power Gener., vol. 16, no. 6, pp. 1220–1245, 2022. https://doi.org/10.1049/rpg2.12435.
S. Oladipo, Y. Sun, and Z. Wang, “An effective hFPAPFA for a PIDA-based hybrid loop of Load Frequency and terminal voltage regulation system,” Proceedings of the 2021 IEEE PES/IAS PowerAfrica, PowerAfrica 2021, 2021. https://doi.org/10.1109/PowerAfrica52236.2021.9543348.
H. Yapici and N. Cetinkaya, “A new meta-heuristic optimizer: Pathfinder algorithm,” Appl. Soft Comput. J., vol. 78, pp. 545–568, 2019. https://doi.org/10.1016/j.asoc.2019.03.012.
H. Yapici, “Solution of optimal reactive power dispatch problem using pathfinder algorithm,” Eng. Optim., vol. 53, no. 11, pp. 1946–1963, 2021. https://doi.org/10.1080/0305215X.2020.1839443.
P. Subbaraj and P. N. Rajnarayanan, “Optimal reactive power dispatch using self-adaptive real coded genetic algorithm,” Electr. Power Syst. Res., vol. 79, no. 2, pp. 374–381, 2009. https://doi.org/10.1016/j.epsr.2008.07.008.
C. H. Liang, C. Y. Chung, K. P. Wong, X. Z. Duan, and C. T. Tse, “Study of differential evolution for optimal reactive power flow,” IET Gener. Transm. Distrib., vol. 1, no. 2, pp. 253–260, 2007. https://doi.org/10.1049/iet-gtd:20060123.
S. Pandya and R. Roy, “Particle swarm optimization based optimal reactive power dispatch,” Proceedings of the 2015 IEEE Int. Conf. Electr. Comput. Commun. Technol. ICECCT 2015, 2015. https://doi.org/10.1109/ICECCT.2015.7225981.
Y. Li, Y. Wang, and B. Li, “A hybrid artificial bee colony assisted differential evolution algorithm for optimal reactive power flow,” Int. J. Electr. Power Energy Syst., vol. 52, no. 1, pp. 25–33, 2013. https://doi.org/10.1016/j.ijepes.2013.03.016.
M. Nasouri Gilvaei, H. Jafari, M. Jabbari Ghadi, and L. Li, “A novel hybrid optimization approach for reactive power dispatch problem considering voltage stability index,” Eng. Appl. Artif. Intell., vol. 96, no. October, 2020. https://doi.org/10.1016/j.ijepes.2013.03.016.
How to Cite
LicenseInternational Journal of Computing is an open access journal. Authors who publish with this journal agree to the following terms:
• Authors retain copyright and grant the journal 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) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.