Tiwari et al. Res. Trends Int. J. Technol. Innov., January - March 2026, 1 (1) : 72-80
1Department of Electrical and Electronics Engineering, National Institute of Technology Karnataka, Surathkal, India; 2Department of Electrical Engineering, Delhi Technological University, New Delhi, India
Article History
Accepted : 10 Mar 2026
Published : 28 Mar 2026
Publication Issue
Volume 1, Issue 1
January - March 2026
Page Number72–80
Improper placement and sizing of distributed generation units can worsen rather than improve voltage profiles and losses in radial distribution networks. This paper applies the Grey Wolf Optimization metaheuristic to simultaneously determine optimal location and capacity of three solar-based DG units on the IEEE 33-bus and 69-bus test systems. The proposed method reduced real power losses by 62.4 percent on the 33-bus system and improved the minimum bus voltage from 0.913 pu to 0.968 pu, outperforming particle swarm optimisation and genetic algorithm baselines reported in prior studies.
Keywords - distributed generation, grey wolf optimization, power loss reduction, radial distribution network, voltage profile
The integration of distributed generation into radial distribution networks can significantly reduce line losses and improve voltage regulation when units are optimally sited, but naive or load-proportional placement can introduce reverse power flow and voltage violations.
The DG placement and sizing problem was formulated to minimise total real power loss subject to voltage and thermal constraints, and solved using Grey Wolf Optimization with a population of 30 search agents over 100 iterations on the IEEE 33-bus and 69-bus radial test systems, with backward-forward sweep load flow used for fitness evaluation.
On the 33-bus system, optimal placement of three DG units reduced real power losses from 202.7 kW to 76.2 kW (62.4 percent reduction) and raised the minimum bus voltage from 0.913 pu to 0.968 pu. Comparable improvements of 58.9 percent loss reduction were observed on the 69-bus system, exceeding results reported for PSO and GA in comparable prior studies.
Grey Wolf Optimization proves effective and computationally efficient for joint DG siting and sizing in distribution networks. Future work will extend the formulation to include time-varying load and DG output profiles.
[1] Mirjalili S. et al., Grey Wolf Optimizer, Advances in Engineering Software, 2014. [2] Kansal S. et al., Optimal placement of distributed generation in distribution networks, IJEPES, 2013. [3] Gozel T. and Hocaoglu M. H., An analytical method for the sizing and siting of DG, Electric Power Systems Research, 2009.
© 2026 The Author(s). Published by IJEIA Editorial Office. This is an open access article under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
Manoj Tiwari, Ritu Chawla (2026). Optimal Placement of Distributed Generation Units in Radial Distribution Networks Using Grey Wolf Optimization. IJEIA, 1(1), 72-80.