A New Hybrid Cuckoo Search-Artificial Bee Colony Approach for Optimal Placing of UPFC Considering Contingencies

Siva Sankar Akumalla*, Bharath Kumar Polineni **, Sujatha Peddakotla ***
* Senior Lecturer, Department of Electrical and Electronics Engineering, Government Polytechnic, Proddatur, Kadapa, Andhra Pradesh , India.
** Lecturer, Department of Electrical and Electronics Engineering, JNTUA College of Engineering, Ananthapuramu, Andhra Pradesh, India.
*** Professor, Department of Electrical and Electronics Engineering, JNTUA College of Engineering, Ananthapuramu, Andhra Pradesh, India.
Periodicity:February - April'2018
DOI : https://doi.org/10.26634/jps.6.1.14308


The Optimal Power Flow (OPF) is a specialised area of power system, that generally requires solving nonlinear optimization problems. The OPF formulation, when includes generators' operating constraints and Flexible AC Transmission Systems (FACTS) devices becomes profoundly complicate multi-objective optimization problem. To target the multi-objective solution, Metaheuristic algorithms have been favored as they give promising results in many such optimization cases. Herein, developing and evaluating a new hybrid method, such as a blend of two simulation-based metaheuristic methods, Cuckoo-Search (CS) and Artificial Bee Colony (ABC) algorithms was focussed. This approach helps the engineer in best locating Unified Power Flow Controller (UPFC), the versatile FACTS' controller, in a multimachine power system to preserve voltage stability and reduce the line power losses under contingencies. The CS algorithm, which was first presented in the mid of 2009 as a novel optimization technique, is motivated by the compel behavior, clearly, brood parasitism of the cuckoos. Here, the ABC feature alters the levy flight behavior and, in consequence, the searching ability of the CS algorithm is enhanced. The test results, when examined on IEEE 30-bus benchmark system, reveal the notable going of the combined approach over the original CS method.


Optimal Power Flow(OPF), Cuckoo Search (CS), Artificial Bee Colony (ABC), UPFC, Real Power Losses

How to Cite this Article?

Akumalla, S, S., Polineni, B. K., and Peddakotla, S. (2018). A New Hybrid Cuckoo Search-Artificial Bee Colony Approach for Optimal Placing of UPFC Considering Contingencies. i-manager’s Journal on Power Systems Engineering, 6(1), 26-34. https://doi.org/10.26634/jps.6.1.14308


[1]. Abd-Elazim, S. M., & Ali, E. S. (2016). Optimal location of STATCOM in multimachine power system for increasing loadability by Cuckoo Search algorithm. International Journal of Electrical Power & Energy Systems, 80, 240- 251.
[2]. Abdelaziz, A. Y., Taha, A. T. M., Mostafa, M. A., & Hassan, A. M. (2013). Fuzzy logic based power system contingency ranking. International Journal of Intelligent Systems and Applications, 5(3), 1-12.
[3]. Abido, M. A. (2009). Power system stability enhancement using FACTS controllers: A Review. The Arabian Journal for Science and Engineering, 34(1B), 153-172.
[4]. Armaghani, S., Amjady, N., & Abedinia, O. (2015). Security constrained multi-period optimal power flow by a new enhanced artificial bee colony. Applied Soft Computing, 37, 382-395.
[5]. Cai, L. J., Erlich, I., & Stamtsis, G. (2004, October). Optimal choice and allocation of FACTS devices in deregulated electricity market using genetic algorithms. In Power Systems Conference and Exposition, 2004. IEEE PES (pp. 201-207). IEEE.
[6]. Cha, S. H., & Tappert, C. C. (2009). A genetic algorithm for constructing compact binary decision trees. Journal of Pattern Recognition Research, 4(1), 1-13.
[7]. Chowdhury, B. H., & Rahman, S. (1990). A review of recent advances in economic dispatch. IEEE Transactions on Power Systems, 5(4), 1248-1259.
[8]. Eberhart, R., & Kennedy, J. (1995, October). A new optimizer using particle swarm theory. In Micro Machine and Human Science, 1995. MHS'95., Proceedings of the Sixth International Symposium on (pp. 39-43). IEEE.
[9]. Gerbex, S., Cherkaoui, R., & Germond, A. J. (2001). Optimal location of multi-type FACTS devices in a power system by means of genetic algorithms. IEEE Transactions on Power Systems, 16(3), 537-544.
[10]. Karaboga, D., & Akay, B. (2009). A comparative study of artificial bee colony algorithm. Applied Mathematics and Computation, 214(1), 108-132.
[11]. Kefayat, M., Ara, A. L., & Niaki, S. N. (2015). A hybrid of Ant Colony Optimization and Artificial Bee Colony algorithm for probabilistic optimal placement and sizing of distributed energy resources. Energy Conversion and Management, 92, 149-161.
[12]. Lam, B. P., & Ringlee, R. J. (1988). Implications of reliability worth. International Journal of Electrical Power & Energy Systems, 10(3), 201-206.
[13]. Moghavvemi, M., & Faruque, M. O. (2000). Effects of FACTS devices on static voltage stability. In TENCON 2000. Proceedings (Vol. 2, pp. 357-362). IEEE.
[14]. Orfanogianni, T., & Bacher, R. (2003). Steady-state optimization in power systems with series FACTS devices. IEEE Transactions on Power Systems, 18(1), 19-26.
[15]. Pardalos, P. M., Romeijn, H. E., & Tuy, H. (2000). Recent developments and trends in global optimization. Journal of Computational and Applied Mathematics, 124(1), 209-228.
[16]. Parizad, A., Khazali, A., & Kalantar, M. (2009, November). Application of HSA and GA in optimal placement of FACTS devices considering voltage stability and losses. In Electric Power and Energy Conversion Systems, 2009. EPECS'09. International Conference on (pp. 1-7). IEEE.
[17]. Rashedi, E., Nezamabadi-Pour, H., & Saryazdi, S. (2009). GSA: A gravitational search algorithm. Information Sciences, 179(13), 2232-2248.
[18]. Singh, B., Sharma, N. K., & Tiwari, A. N. (2010). A comprehensive survey of optimal placement and coordinated control techniques of FACTS controllers in multi-machine power system environments. Journal of Electrical Engineering and Technology, 5(1), 79-102.
[19]. Sode-Yome, A., Mithulananthan, N., & Lee, K. Y. (2005). Static voltage stability margin enhancement using STATCOM, TCSC and SSSC. In Transmission and Distribution Conference and Exhibition: Asia and Pacific, 2005 IEEE/PES (pp. 1-6). IEEE.
[20]. Sonmez, Y., Guvenc, U., Duman, S., & Yorukeren, N. (2012, July). Optimal power flow incorporating FACTS devices using Gravitational Search Algorithm. In Innovations in Intelligent Systems and Applications (INISTA), 2012 International Symposium on (pp. 1-5). IEEE.
[21]. Yang, X. S., & Deb, S. (2009, December). Cuckoo search via Lévy flights. In Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on (pp. 210-214). IEEE.
[22]. Yang, X. S., & Deb, S. (2014). Cuckoo search: Recent advances and applications. Neural Computing and Applications, 24(1), 169-174.

Purchase Instant Access

Single Article

North Americas,UK,
Middle East,Europe
India Rest of world
Pdf 35 35 200 20
Online 35 35 200 15
Pdf & Online 35 35 400 25

If you have access to this article please login to view the article or kindly login to purchase the article
Options for accessing this content:
  • If you would like institutional access to this content, please recommend the title to your librarian.
    Library Recommendation Form
  • If you already have i-manager's user account: Login above and proceed to purchase the article.
  • New Users: Please register, then proceed to purchase the article.