Abstract
This paper presents an Enhanced Cuckoo Search Algorithm (ECSA) to optimally place and size Distributed Generation (DG) in radial distribution systems to minimize real power loss within operating constraints. The proposed ECSA has exponentially decaying adaptive Lévy flights, constraint-aware solution repair with dynamic penalty coefficients, and diversity-directed stochastic replacement to enhance search robustness and convergence speed. It was tested with 30 independent runs on the IEEE 33-bus, IEEE 69-bus, and a practical Nigerian 32-bus distribution network. The simulations show that the ECSA lowers the active power loss of the IEEE 33-bus system from 201.58 kW to 102.75 kW (49.03%), and the IEEE 69-bus system from 224.60 kW to 81.59 kW (61.67%), both statistically significant at p> 0.01. For the 32-bus network of Imalefalafia, losses were reduced from 95.07 kW to 14.78 kW (84.45%), and the minimum voltage was increased from 0.9524 p.u. to 0.9821 p.u. For all test systems, the proposed ECSA consistently outperformed fifteen benchmark metaheuristic algorithms in convergence speed, solution quality, and strength, making it useful for DG planning applications.
Recommended Citation
Ayanlade, Samson Oladayo; Jimoh, Abdulrasaq; Olarewaju, Richard Oladayo; and Okakwu, Ignatius Kema
(2026)
"ENHANCED CUCKOO SEARCH-BASED OPTIMIZATION FOR SINGLE DISTRIBUTED GENERATION PLACEMENT AND SIZING IN RADIAL DISTRIBUTION SYSTEMS,"
Al-Bahir: Vol. 8:
Iss.
2, Article 1.
Available at: https://doi.org/10.55810/2313-0083.1123
References
[1] Ayanlade SO, Jimoh A, Ezekiel SO, Babatunde AA. Voltage profile improvement and active power loss reduction through network reconfiguration using dingo optimizer. 2023. Cham.
[2] Ariyo FK, Ayanlade SO, Adeagbo AP, Jimoh A, Adebayo MT. Assessment of the impact of distribution generation on radial distribution network protection system. Niger J Technol 2025;44(3):471—83.
[3] Ayanlade SO, Jimoh A, Ogunwole EI, Aremu A, Jimoh AB, Owolabi DE. Simultaneous network reconfiguration and capacitor allocations using a novel dingo optimization algorithm. Int J Electr Comput Eng (IJECE). 2023;13(3): 2384—95.
[4] Jimoh A, Ayanlade SO, Ariyo FK, Aremu A, Jimoh BA, Jimoh MA. Capacitor allocation optimization for improved distribution network performance. In: Proc 2nd Int Conf Mechatron Electr Eng (MEEE); 2023. p. 1—6.
[5] Srivastava A, Manas M, Dubey RK. Electric vehicle integration's impacts on power quality in distribution network and associated mitigation measures: a review. J Eng Appl Sci 2023;70:32.
[6] Chethan M, Kuppan R. A review of FACTS device implementation in power systems using optimization techniques. J Eng Appl Sci 2024;71(1):18.
[7] Ayanlade SO, Ariyo FK, Jimoh A, Akindeji KT, Adetunji AO, Ogunwole EI, Owolabi DE. Optimal allocation of photovoltaic distributed generations in radial distribution networks. Sustainability 2023;15(18):13933.
[8] Osabohien RW, Uhunmwangho R. Assessing the impacts of distributed generation on the protection scheme of a distribution network: trans Amadi 33 kV distribution network as a case study. Niger J Technol 2018;37(1):209—15.
[9] Kansal S, Kumar V, Tyagi B. Optimal placement of different type of DG sources in distribution networks. Int J Electr Power Energy Syst 2013;53:752—60.
[10] Borges L, Falcao DM. Optimal distributed generation allocation for reliability, losses, and voltage improvement. Int J Electr Power Energy Syst 2006;28(6):413—20.
[11] Barutcu IC, Sharma G, Gandhi RV, Jadoun VK, Garg A. Investigations on solar PV integration and associated power quality challenges in distribution systems through the application of MCS and GA. J Eng Appl Sci 2024;71(1):118.
[12] Murthy VVSN, Kumar A. Comparison of optimal DG allocation methods in radial distribution systems based on sensitivity approaches. Int J Electr Power Energy Syst 2013; 53:450—67.
[13] Alvarado-Reyes S, Villar-Yacila P, Fiestas H. Imperialist competitive algorithm applied to the optimal integration of photovoltaic distributed generation units into a microgrid. e-Prime - Adv Electr Eng Electron Energy 2022;2:100086.
14] Reddy PDP, Reddy VV, Manohar TG. Whale optimization algorithm for optimal sizing of renewable resources for loss reduction in distribution systems. Renew Wind Water Solar 2017;4:1—13.
[15] Kansal S, Kumar V, Tyagi B. Hybrid approach for optimal placement of multiple DGs of multiple types in distribution networks. Int J Electr Power Energy Syst 2016;75:226—35. [16] Selim A, Kamel S, Mohamed AA, Elattar EE. Optimal allocation of multiple types of distributed generations in radial distribution systems using a hybrid technique. Sustainability 2021;13(12):6644. [17] Ali AH, Youssef AR, George T, Kamel S. Optimal DG allocation in distribution systems using Ant lion optimizer. In: 2018 Int Conf Innovative Trends Comput Eng (ITCE); 2018. p. 324—31
. [18] Sobieh M, Mandour M, Saied EM, Salama MM. Optimal number, size and location of distributed generation units in radial distribution systems using Grey Wolf optimizer. Int Electr Eng J 2017;7(9):2367—76.
[19] Hung Q, Mithulananthan N. Multiple distributed generator placement in primary distribution networks for loss reduction. IEEE Trans Ind Electron 2011;60(4):1700—8.
[20] Mahmoud K, Yorino N, Ahmed A. Optimal distributed generation allocation in distribution systems for loss minimization. IEEE Trans Power Syst 2015;31(2):960—9.
[21] El-Fergany A. Optimal allocation of multi-type distributed generators using backtracking search optimization algorithm. Int J Electr Power Energy Syst 2015;64:1197—205.
[22] Kashyap M, Mittal A, Kansal S. Optimal placement of distributed generation using genetic algorithm approach. In: Proc 2nd Int Conf Microelectron Comput Commun Syst (MCCS 2017); 2019. p. 587—97
. [23] Aman MM, Jasmon GB, Bakar AHA, Mokhlis H. A new approach for optimum simultaneous multi-DG units placement and sizing based on maximization of system loadability using HPSO algorithm. Energy 2014;66:202—15.
[24] Bayat A, Bagheri A. Optimal active and reactive power allocation in distribution networks using a novel heuristic approach. Appl Energy 2019;233:71—85.
[25] Nowdeh SA, et al. Fuzzy multi-objective placement of renewable energy sources in distribution system with objective of loss reduction and reliability improvement using a novel hybrid method. Appl Soft Comput 2019;77: 761—79.
26] Nassar SM, Saleh AA, Eisa AA, Abdallah EM, Nassar IA. Optimal allocation of renewable energy resources in distribution systems using meta-heuristic algorithms. Results Eng 2025;25:104276.
[27] Adegboye OR, Ülker ED. Hybrid artificial electric field employing cuckoo search algorithm with refraction learning for engineering optimization problems. Sci Rep 2023;13: 4098.
[28] Ikeli NH, Ashigwuike CE. Enhancing power system loadability using improved PSO/ABC, ABC/BFO, PSO/BFO and CS/BFO hybrid techniques. J Electr Syst Inf Technol 2025;12: 16.
[29] Pujari HK, Rudramoorthy M, Gopi RR, Mishra S, Alluraiah NC, Vaishali NB. Optimal reconfiguration, renewable DGs, and energy storage units' integration in distribution systems considering power generation uncertainty using hybrid GWO—SCA algorithms. Int J Model Simul 2024;44(1):1—33.
[30] Zain AZM, Ridzuan MIM, Roslan NNR, Ali NZM. A comparative study of reliability and loss minimization in DG placement using hybrid analytical—grey wolf optimization. In: Proc IEEE 9th Int Conf Eng Technol Appl Sci (ICETAS); 2024. p. 1—5. https://doi.org/10.1109/ICETAS62372.2024.11120038. Bahrain.
[31] Rahman NAA, Hamid ZA, Salim NA, Musirin I. Multiobjective optimal DG placement and sizing in distribution systems using LSF—MALO: a study on various DG configurations and load. J Theor Appl Inf Technol 2025;103(17): 1—14. AL-BAHIR (JOURNAL FOR ENGINEERING AND PURE SCIENCES) 2026;8:124—144 143
[32] Abdul Rahman NA, Hamid Z, Salim NA. Optimal placement of distributed generation in distribution network: a review on hybrid techniques. J Electr Electron Syst Res 2025; 25:80—8.
[33] Yang XS, Deb S. Engineering optimisation by cuckoo search. Int J Math Model Numer Optim 2010;1(4):330—43.
[34] Yang XS, Deb S. Cuckoo search via Levy flights. In: 2009 world congress on Nature & Biologically Inspired Computing (NaBIC); 2009. p. 210—4.
[35] Yin S, Tu J, Chen X. A new tree-based data aggregation method in wireless sensor networks using Ant Colony Optimization and Cuckoo search algorithms. J Eng Appl Sci 2025;72(1):83.
[36] Ghosh M, Kumar S, Mandal S, Mandal KK. Optimal sizing and placement of DG units in radial distribution system using Cuckoo Search Algorithm. Int J Appl Eng Res 2017; 12(1):362—9.
[37] Tan WS, Hassan MY, Majid MS, Rahman HA. Allocation and sizing of DG using Cuckoo Search algorithm. In: Proc IEEE Int Conf Power Energy (PECon); 2012. p. 133—8.
[38] Nazri AFHA, Zulkefle H, Musirin I, Ismail NL, Halim MA, Kamari NAM, Abdullah A, Kasinathan V, Mustapha A. Integrated cuckoo—evolutionary programming-based technique incorporating distribution generation for economic dispatch in power system. Int J Integr Eng 2025;17(2): 151—63.
[39] Ayanlade SO, Komolafe OA. Distribution system voltage profile improvement based on network structural characteristics. In: Proc Faculty Technol Conf (OAUTEKCONF 2019). Nigeria: OAU, Ile-Ife; 2019.
Included in
Bioresource and Agricultural Engineering Commons, Electrical and Electronics Commons, Other Electrical and Computer Engineering Commons, Power and Energy Commons





Indexed in: