Regular Article

An enhanced EDBO-based planning for optimal placement and sizing of wind turbine-based distributed generators in unbalanced radial distribution system

¹ Electrical Engineering Department, Jamia Millia Islamia, New Delhi, India
² Electrical Engineering Department, JSS Academy of Technical Education, Noida, India
³ Electrical and Electronics Engineering Department, KIET Group of Institutions, Ghaziabad, India

^* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Received: 28 February 2025
Accepted: 28 January 2026

Abstract

Background: Researchers are actively addressing the environmental impact of fossil fuels by leveraging Renewable Energy Sources (RES), particularly wind power. However, the inherent variability of wind energy, driven by unpredictable wind speeds, presents challenges for ensuring the reliability of distribution systems. Objective: Efficiently determining optimal locations and capacities for integrating RES into distribution networks is crucial for realizing benefits such as improved voltage profiles, congestion mitigation, enhanced reliability, and reduced emissions. Placing RES in suboptimal locations may yield undesirable outcomes. Methodology: To address the issue, a nature-based optimization approach called Enhanced Dung Beetle Optimisation (EDBO) is introduced for selecting the most suitable positions and sizes for Wind Turbines (WT) within distribution systems. The optimization considers technical constraints such as wind power output, voltage, and power flow limits, and load balancing requirements. Test system: This optimization approach is applied to optimize WT placement and sizing within distribution systems, showcasing its effectiveness through simulation tests on IEEE-13 and IEEE-34 bus systems. Results and conclusion: The proposed method significantly reduces power loss compared to all other conventional techniques used in the IEEE-13 bus system and the IEEE-34 bus systems. Additionally, the technique enhances sustainable and reliable energy distribution in the context of WT integration.