Citation

P, Rajakumar and PM, Balasubramaniam and V, Ravi and Yumurtacı, Mehmet and Gulbarga, Mohammad Imtiyaz and Alam, Mohammad Mukhtar and Wee, Kuok Kwee and Keçebaş, Ali (2026) Hybrid sensitivity-driven enhanced modified ant lion optimizer framework for multi- distributed generation allocation in radial distribution networks. Energy Reports, 15. p. 109144. ISSN 2352-4847

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Abstract

Optimal siting and sizing of distributed generation (DG) units in radial power distribution networks (RPDNs) remain a critical challenge due to their nonlinear, multi-objective nature. Existing optimization approaches often struggle with computational inefficiencies, premature convergence, and limited adaptability across varying network scales. Addressing these limitations, this study proposes a novel hybrid framework that integrates Active Power Loss Sensitivity (APLS) and Voltage Sensitivity Index (VSI)-based bus preselection with an Enhanced Modified Ant Lion Optimizer (EMALO) for efficient multi-DG allocation. The proposed method leverages chaosbased initialization, L´evy-flight global search, and an elitist memory pool to enhance convergence reliability and solution diversity. A multi-objective fitness function is employed to minimize real power loss (RPL) and improve voltage profiles (VP), evaluated through Pareto-optimal approach. The methodology is rigorously tested on IEEE 69-bus and 118-bus systems and the practical Cairo-59-bus network using real-time load and PV generation profiles. Results reveal that EMALO achieves up to 69.12% and 96.52% RPL reductions for PV and WT scenarios respectively on the 69-bus system, surpassing conventional ALO, ABC, and BAT algorithms in both technical and computational performance. In the Cairo-59 case, EMALO reduced losses by 87%, demonstrating its practical viability. By addressing key research gaps in adaptive bus selection and robust multi-objective optimization, this study contributes a scalable, performance-driven solution for enhancing grid reliability and energy efficiency in modern RPDNs.

Item Type:	Article
Uncontrolled Keywords:	Radial distribution networks
Subjects:	Q Science > QC Physics > QC501-766 Electricity and magnetism
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	02 Apr 2026 06:20
Last Modified:	06 Apr 2026 06:01
URII:	http://shdl.mmu.edu.my/id/eprint/15660

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