An Improved Cuckoo Search Algorithm for Voltage Stability Enhancement in Power Transmission Networks

Authors: Reza Sirjani, Nobosse Tafem Bolan

Abstract:

Many optimization techniques available in the literature have been developed in order to solve the problem of voltage stability enhancement in power systems. However, there are a number of drawbacks in the use of previous techniques aimed at determining the optimal location and size of reactive compensators in a network. In this paper, an Improved Cuckoo Search algorithm is applied as an appropriate optimization algorithm to determine the optimum location and size of a Static Var Compensator (SVC) in a transmission network. The main objectives are voltage stability improvement and total cost minimization. The results of the presented technique are then compared with other available optimization techniques.

Keywords: Cuckoo search algorithm, optimization, power system, var compensators, voltage stability.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1339243

References:

[1] Mohammadi, M., Gitizadeh, M. and Roosta, A. (2012). Dynamic Stability Improvement of a Power System Incorporating DFIG Wind Power Plant Using Optimized Control Parameters of a SVC. IEEE International Power Engineering and Optimization Conference (PEOCO), 416-421.
[2] Dhal, P. K. and Rajan, C. C. A. (2012). Transient Stability Improvement Using Neuro Fuzzy Controller Design for STATCOM. IEEE International Conference on Advance in Engineering and Management (ICAESM), 2(2), 37-45.
[3] Sunil, T. P. and Loganathan, N. (2012). Power Quality Improvement of a Grid Connected Wind Energy Conversion System with Harmonics Reduction Using FACTS Devices. IEEE International Conference on Advances in Engineering Management (ICAESM), 415.
[4] Duttal, P. and Sinha, A. K. (2006). Voltage Stability Constrained Multi-objective Optimal Power Flow using Particle Swarm Optimization. First International Conference on Industrial and Information Systems (ICIIS), 161-166.
[5] Benabida, R., Boudourb, M. and Abidoc, M.A. (2009). Optimal location and setting of SVC and TCSC devices using non-dominated sorting particle swarm optimization. Electric Power Systems Research, 79, 1668–1677.
[6] Roy, R. and Jadhav, H.T. (2015). Optimal power flow solution of power system incorporating stochastic wind power using Gbest guided artificial bee colony algorithm. Electrical Power and Energy Systems, 64, 562–578.
[7] Sirjani, R., Mohamed, A. and Shareef, H. (2012). Optimal allocation of shunt Var compensators in power systems using a novel global harmony search algorithm. Electrical Power and Energy Systems, 43, 562–572.
[8] Sirjani, R., Mohamed, A. and Shareef, H. (2013). Optimal Placement of Var Compensators in Transmission Networks Using Heuristic Optimization Techniques. LAMBERT Academic Publishing, 7-22.
[9] Laifa, A. and Medoued, A. (2013). Optimal FACTS Location to Enhance Voltage Stability Using Multi-Objective Harmony Search. 2013 3rd International Conference on Electric Power and Energy Conversion Systems, 1-6.
[10] Arcanjo, D. N. et al. (2012). Cuckoo Search Optimization Technique Applied to Capacitor Placement on Distribution System Problem. images,” IEEE Trans. Image Process., vol. 10, no. 5, pp. 767-782, May 2001.
[11] Kumar, A. and Chakarverty, S. (2011). Design optimization using Genetic Algorithm and Cuckoo Search. IEEE International Conference on Electro/Information Technology, 1-5.
[12] El-Fergany, A. A. and Abdelaziz, A. Y. (2014). Capacitor Allocations in Radial Distribution Networks Using Cuckoo Search Algorithm. IET Gener. Transm. Distrib., 8(2), 223–232.
[13] Lenin, K., Reddy, B. R. and Kalavathi, M. S. (2014). Improved Cuckoo Search Algorithm for Solving Optimal Reactive Power Dispatch Problem. International Journal of Research in Electronics and Communication Technology (IJRECT 2014), 1(1), 20-24.
[14] Xing-shi, H., Li, N. and Xin-She, Y. (2014). Non-dominated Sorting Cuckoo Search for Multi-Objective Optimization. IEEE publication.
[15] Xin-She, Y. and Deb, S. (2009). Cuckoo search via Levy flights. Proc. Of World Congress on Nature & Biologically Inspired Computing, India. IEEE Publications, 210-214.
[16] Xin-She, Y. and Deb, S. (2010). Engineering Optimization by Cuckoo Search. Int. J. Mathematical Modelling and Numerical Optimization, 1(4), 330–343.
[17] Zhang, Z. and Chen, Y. J. (2014). An Improved Cuckoo Search Algorithm with Adaptive Method. 2014 Seventh International Joint Conference on Computational Sciences and Optimization, 204-207.