OPTIMAL PLACEMENT AND SIZE OF DISTRIBUTED GENERATION IN RADIAL DISTRIBUTION SYSTEM USING WHALE OPTIMIZATION ALGORITHM

Authors

  • Sovann Ang Faculty of Electrical Engineering, National Polytechnic Institute of Cambodia, Phnom Penh, 12000, Cambodia.
  • Uthen Leeton School of Electrical Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand.

Keywords:

Distribution generation, whale optimization algorithm, radial distribution network 1

Abstract

Distributed generation (DG) is small-scale energy generation which is closely installed to a load area. It is widely preferred in distribution networks due to its potential solution for loss mitigation and voltage profile improvement. The purposes of this research paper are to find the optimal location and size of the DG in a distribution system. The Newton-Raphson power flow method is used to solve the power flow in the system. In this paper, the overall active power loss minimization in the system is the objective function. The optimal location and sizing of the DG can be obtained by using, respectively, the fast voltage stability index and whale optimization algorithm which is the most recent metaheuristic optimization algorithm based on the natural hunting behaviour of the humpback whale. Moreover, the proposed algorithm is evaluated through 15 and 33 buses of the radial distribution networks. Furthermore, 3 kinds of the DG contribution are considered to compare the efficiency and performance. The results show the effectiveness and great performance of the proposed method in determining the optimal size and location of the DG in distribution systems.

References

Anumaka, M.C. (2012). Analysis of technical losses in electrical power system (Nigerian 330KV network as a case study). Int. J. Recent Res. Appl. Studies, 12:1-8.

Aref, A. and Davoudi, M. (2012). Optimal DG placement in distribution network using intelligent systems. Energy and Power Engineering, 4:92-98.

Burchett, R.C., Happ, H.H., and Vierath, D.R. (1984). Quadratically convergent optimal power flow. IEEE T. Power Ap. Syst., 103:3,267-3,276.

Cai, G., Zhang, Y., and Ren, Z. (2007). Optimal power flow algorithm based on nonlinear multiple centrality corrections interior point method. Transactions of China Electrotechnical Society, 22:133-139.

Carpentier, J. (1979). Optimal power flows. Int. J. Elec. Power., 1:3-15.

Celli, G. and Pilo, F. (2001). Optimal distributed generation allocation in MV distribution networks. Proceedings of the 22nd IEEE Power Engineering Society. International Conference on Power Industry Computer Applications; May 20-24, 2001; Sydney, NSW, Australia, p. 81-86.

Chambers, A. (2001). Distributed Generation: a Nontechnical Guide. 1st ed. PennWell Corp., Tulsa, OK, USA, 250p.

Chiradeja, P. (2005). Benefit of distributed generation: a line loss reduction analysis. Proceedings of the IEEE/PES Transmission and Distribution Conference and Exposition: Asia and Pacific; August 18, 2005; Dalian, China, p. 1-5.

Das, D., Kothari, D.P., and Kalam, A. (1995). Simple and efficient method for load flow solution of radial distribution network. Int. J. Elec. Power., 17(5):335-346.

Dommel, H.W. and Tinney, W.F. (1968). Optimal power flow solutions. IEEE T. Power Syst., 87:1,866-1,876.

Dondi, P., Bayoumi, D., Haederli, C., Julian, D., and Suter, M. (2002). Network integration of distributed power generation. J. Power Sources, 106:1-9.

Dulau, L.I., Abrudean, M., and Bica, D. (2015). Optimal location of a distributed generator for power losses improvement. Procedia Technology, 22:734-739.

Georgilakis, P.S. and Hatziargyriou, N.D. (2013). Optimal distributed generation placement in power distribution networks: Models, methods and future research. IEEE T. Power Syst., 28(3):3,420-3,428.

Hazra, J. and Sinha, A.K. (2011). A multi-objective optimal power flow using particle swarm optimization. Eur. T. Electr. Pow., 21:1,028-1,045.

Hu, H., Bai, Y., and Xu, T. (2016). A whale optimization algorithm with inertia weight. World Scientific and Engineering Academy and Society Transactions on Computers, 15:319-326.

Karaboga, D. (2005). An idea based on honey bee swarm for numerical optimization. Technical Report-TTR06, Erciyes University Press, Kayseri, Turkey.

Konak, A., Coit, D.W., and Smith, A.E. (2006). Multi-objective optimization using genetic algorithms: a tutorial. Reliab. Eng. Syst. Safe., 21:992-1,007.

Mirjalili, S. and Lewis, A. (2016). The whale optimization algorithm. Adv. Eng. Softw., 95:51-67.

Mishra, A. and Bhandakkar, A. (2014). Selection of optimal location and size of distributed generation in distribution system using particle swarm optimization. Int. J. Eng. Res. Technol., 3(1):2,008-2,013.

Mota-Palomino, R. and Quintana, V.H. (1986). Sparse reactive power scheduling by a penalty function-linear programming technique. IEEE T. Power Syst., 1:31-39.

Musirin, I. and Abdul Rahman, T.K. (2002). Novel fast voltage stability index (FVSI) for voltage stability analysis in power transmission system. Proceeding of Conference on Research and Development; july 16-17, 2002; Shah Alam, Malaysia, p. 265-268.

Pandy, D. and Bhadoriya, J.S. (2014). Optimal placement & sizing of distributed generation to minimize active power loss using particle swarm optimization. Int. J. Sci. Technol. Res., 3:246-254.

Prakash, P. and Khatod, D.K. (2016). An analytical approach for optimal sizing and placement of the distribued generation in radial distribution systems. Proceedings of the 1st IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems; July 4-6, 2016; Delhi, India, p. 1-5.

Prakash, D.B. and Lakshminarayana, C. (2017). Optimal siting of capacitors in radial distribution network using whale optimization algorithm. Alexandria Eng. J., 56:499-509.

Reddy, P.D.P., Reddy, V.C.V., and Manohar, T.G. (2017). Whale optimization algorithm for optimal sizing of renewable resources for loss reduction in distribution systems. Renewables: Wind, Water, and Solar. 4:1-13.

Shaddiq, S., Santoso, D.B., Alfarobi, F.F., Sarjiya, and Hadi, S.P. (2016). Optimal capacity and placement of distributed generation using metaheuristic optimization algorithm to reduce power losses in Bantul distribution system, Yogyakarta. Proceedings of the 8th International Conference on Information Technology and Electrical Engineering; October 5-6, 2016; Yogyakarta, Indonesia, p. 1-5.

Sharawi, M., Zawbaa, H.M., and Emary, E. (2017). Feature selection approach based on whale optimization algorithm. Proceedings of the 9th International Conference on Advanced Computational Intelligence; February 4-6, 2017; Doha, Qatar, p. 163-168.

Sharma, A.K., Saxena, A., and Tiwari, R. (2017). Maximum loadability estimation for weak bus identification using line stability indices. Int. J. Hybrid Inform. Technol., 10(2):49-60.

Wang, Z. and Xu, Q. (2011). On distribution system planning method for reliability and its application. Proceedings of the 4th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies; July 6-9, 2011; Weihai, China, p. 1,727-1,731.

Watkins, W.A. and Schevill, W.E. (1979). Aerial observation of feeding behaviour in four baleen whales: Eubalaena glacialis, Balaenoptera borealis, Megaptera novaeangliae, and Balaenoptera physalus. J. Mammal., 60:155-163.

Zhang, Y-P., Tong, X-J., Wu, F., Yan, Z., Ni, Y-X., and Chen, S-T. (2004). Study on semi-smooth Newton optimal power flow algorithm based on non-linear complementarity problem function. Proceedings of the Chinese Society for Electrical Engineers, 24:130-135

Downloads

Published

2026-08-28

How to Cite

Ang, S., & Leeton, U. (2026). OPTIMAL PLACEMENT AND SIZE OF DISTRIBUTED GENERATION IN RADIAL DISTRIBUTION SYSTEM USING WHALE OPTIMIZATION ALGORITHM. Suranaree Journal of Science and Technology, 26(1), 1–12. retrieved from https://ph04.tci-thaijo.org/index.php/SUJST/article/view/14535

Issue

Section

Research Article