International Journal of Electrical and Computer Engineering (IJECE) Vol. 15, No. 3, June 2025, pp. 2681~2696 ISSN: 2088-8708, DOI: 10.11591/ijece.v15i3.pp2681-2696  2681 Journal homepage: http://ijece.iaescore.com Cuckoo search algorithm approach for optimal placement and sizing of distribution generation in radial distribution networks Kayode Ojo 1 , Seyi Fanifosi 2 , Awelewa Ayokunle 3 , Isaac Samuel 3 1 Department of Electrical and Electronics Engineering, Lead City University, Ibadan, Nigeria 2 Department of Electrical and Computer Engineering, Klipsch School New Mexico State University, Las Cruces, United Stated of America 3 Department of Electrical and Information Technology, Covenant University, Sango-Ota, Nigeria Article Info ABSTRACT Article history: Received Jun 4, 2024 Revised Jan 30, 2025 Accepted Mar 3, 2025 Radial distribution networks (RDNs) often experience power loss due to improper distribution generation (DG) allocation. Strategic DG placement can reduce power loss, minimize costs, and improve voltage profiles and stability. This research optimizes DG placement and sizing in RDNs using the cuckoo search algorithm (CSA). The objective function considers losses across all network branches, and CSA identifies optimal DG locations and sizes. Tested on IEEE 33-bus, IEEE 69-bus, and Nigeria's Imalefalafia 32-bus RDN, the Cuckoo Search technique results in optimal DG locations at buses 6, 50, and 18 with corresponding sizes of 2.4576, 1.852, and 2.718 MW, respectively. Voltage improvements are 0.9509, 0.9817, and 0.9821 p.u, while total active and reactive power losses for IEEE 33-bus are reduced by 49.03% and 45.00%, and for IEEE 69-bus by 63.67% and 61.14%. The CSA approach significantly enhances voltage profiles and reduces power losses in these networks. Keywords: Cuckoo search algorithm Distribution generation Optimal location Power losses Voltage profile This is an open access article under the CC BY-SA license. Corresponding Author: Awelewa Ayokunle Department of Electrical and Information Technology, Covenant University Sango-Ota, P.M.B 1023, Ogun State, Nigeria Email: ayokunle.awelewa@covenantuniversity.edu.ng 1. INTRODUCTION The efficiency of radial distribution networks (RDNs) is significantly hampered by active power losses occurring across all branches [1]. These losses stem primarily from a high resistance-to-reactance ratio in distribution branches, exacerbated by increasing load demand [2]. To mitigate these losses and enhance network efficiency, researchers have implemented diverse techniques, including deploying capacitors, reconfiguring the network, and integrating distribution static synchronous compensators [3], [4]. However, among these approaches, deploying distribution generators (DGs) has emerged as the most effective. DGs offer the unique capability to contribute both active and reactive power to distribution networks [5]. Notably, type 1 DGs provide these advantages without generating harmful emissions, contributing to environmental sustainability [6]. Yet, optimal planning of DGs is essential to harnessing the full benefits of their deployment in distribution networks. The strategic determination of DG locations and sizes is crucial [7]. Poor planning can adversely affect network functionality. Various planning methods for DGs have surfaced, often utilizing optimization techniques due to the complexity inherent in the configuration of distribution networks with multiple buses and branches [8]. The optimization problems associated with DG planning involve formulating an objective function aimed at minimizing the active power losses and reactive power compensation subject to the operating constraints while adhering to network constraints in RDNs. Solving these problems yields optimal DG locations and sizes, ensuring smooth and efficient RDNs operation [9]–[12]. For voltage profile and voltage