Performance Enhancement of the Radial Distribution System Through Simultaneous Optimal Feeder Reconfiguration and Distributed Generation Placement

Energy loss in distribution networks significantly impacts system efficiency and operational costs. This work focuses on minimizing power losses and improving voltage profiles in an IEEE 33-bus system using a Genetic Algorithm (GA)-based reconfiguration and DG placement. The GA optimally places Distributed Generators (DGs) and reconfigures switches to achieve loss minimization while ensuring voltage stability. Power flow analysis is conducted using the Forward-Backward Sweep method which is introduced for better system analysis. The proposed method establishes an intelligent framework for modern power distribution optimization. A mathematical model is formulated to define power loss minimization and voltage constraints, ensuring network reliability. The Forward-Backward Sweep power flow method is employed to analyse voltage variations and system losses, while a state-space representation is introduced to model the system dynamics. The proposed GA-based approach iteratively enhances network performance by optimizing DG placement and switch configurations simultaneously, leading to better efficiency in power distribution. Results demonstrate that GA significantly reduces losses and enhances voltage profiles compared to conventional techniques.