Sustainability 2022, 14, 11480. https://doi.org/10.3390/su141811480 www.mdpi.com/journal/sustainability Article Performance Enhancement of Radial Power Distribution Networks Using Network Reconfiguration and Optimal Planning of Solar Photovoltaic-Based Distributed Generation and Shunt Capacitors Kandasamy Muthukumar 1 , Thangavel Renugadevi 2, *, Arumugam Thamaraiselvi 3 , Jayaram Jayachandran 1 , Wook-Won Kim 4 and Zong Woo Geem 4, * 1 School of Electrical and Electronics Engineering, SASTRA Deemed University, Thanjavur 613401, India 2 School of Computing, SASTRA Deemed University, Thanjavur 613401, India 3 Sakthi Institute of Information and Management Studies, Pollachi 642001, India 4 Department of Smart City &Energy, Gachon University, Seongnam 13120, Korea * Correspondence: renugadevi@cse.sastra.edu (T.R.); geem@gachon.ac.kr (Z.W.G.) Abstract: In this work, an efficient hybrid optimization approach entitled harmony search and par- ticle artificial bee colony algorithm is proposed to deal with the distribution network reconfigura- tion and solar photovoltaic-based distributed generation and shunt capacitor deployment in power distribution networks to improve the operating performance of power distribution networks. The proposed hybrid algorithm combines the exploration and exploitation capability of both algorithms to achieve optimal results. The optimization problem is formalized which includes distributed gen- eration and shunt capacitor locations, open/close state of switches as discrete decision variables, and the optimum operating point of compensation devices as continuous variables. An efficient span- ning tree approach is utilized to track the optimal topology of the network. The validity of the pro- posed hybrid algorithm in handling the optimal planning problem of the distribution network is assured through eight different operating scenarios at three discrete load levels. The efficiency of the proposed performance enhancement approaches was validated using 69 node and 118 node distribution networks. The obtained results are compared against similar techniques presented in the literature. Keywords: radial power distribution network; distributed generation; harmony search algorithm; optimal radial network topology; particle swarm artificial bee colony algorithm 1. Introduction A power distribution system is a vital component of the power system that transmits electrical power from the substation to the consumer’s end. The operation of the distribu- tion network at a low voltage level with a high current will result in poor operating per- formance of the radial power distribution network (RPDN). Power loss in the RPDN is comparatively higher than that of the transmission network because of the higher R/X ratio and untransposed lengthy feeder lines. Higher resistance in the distribution network escalates more power loss in the feeder lines. This renders the distribution network less efficient in providing quality power to the tail end users. The power utilities follow some traditional approaches to upgrade the performance of the power distribution network by reconfiguring the network, optimally placing substations, transformers, upgrading con- ductors, shunt capacitors (SCs), and distributed generation units (DGs). Citation: Muthukumar, K.; Renugadevi, T.; Thamaraiselvi, A.; Jayachandran, J.; Kim, W.-W.; Geem, Z.W. Performance Enhancement of Radial Power Distribution Networks Using Network Reconfiguration and Optimal Planning of Solar Photovoltaic-Based Distributed Generation and Shunt Capacitors. Sustainability 2022, 14, 11480. https://doi.org/10.3390/su141811480 Academic Editor: Alberto-Jesus Perea-Moreno Received: 16 July 2022 Accepted: 7 September 2022 Published: 13 September 2022 Publisher’s Note: MDPI stays neu- tral with regard to jurisdictional claims in published maps and institu- tional affiliations. Copyright: © 2022 by the authors. Li- censee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and con- ditions of the Creative Commons At- tribution (CC BY) license (https://cre- ativecommons.org/licenses/by/4.0/).