Iterative Artificial Hummingbird Algorithm-Driven Reconfiguration for microgrids under Multiple Interconnection Scenarios

Faculty Engineering Year: 2025
Type of Publication: ZU Hosted Pages:
Authors:
Journal: Energy 360 ELSEVIER Volume: 3
Keywords : Iterative Artificial Hummingbird Algorithm-Driven Reconfiguration , microgrids    
Abstract:
This paper presents a comprehensive study on the reconfiguration of power distribution networks (PDN) within interconnected microgrids (MGs), utilizing the Artificial Hummingbird Algorithm (AHA), Particle Swarm Optimization (PSO), and the Slime Mould Algorithm (SMA) for optimization. The objective is to minimize power loss and improve voltage profiles across the interconnected systems while maintaining a radial topology within each microgrid and the overall interconnection. Building on previous work, which focused solely on horizontal interconnection in two 20-bus systems, this study expands the scope by incorporating vertical and diagonal interconnection scenarios for the 20-bus systems. Additionally, it explores these configurations within a 69-bus system model. Simulation results demonstrate that while all three algorithms improve power loss reduction and voltage stability, AHA consistently outperforms PSO and SMA. The findings contribute to a robust framework for PDN reconfiguration, addressing the complexities of various interconnection configurations and providing valuable insights into enhancing the performance and sustainability of interconnected MGs.
   
     
 
       

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