Network Reconfiguration with Distributed Generation (DG) Integration Using Harmony Search Algorithm

This paper introduces a novel methodology for addressing distribution network reconfiguration challenges incorporating distributed generation (DG) units. The primary objectives involve minimizing active power losses and improving voltage stability across the distribution system. The implementation employs the Harmony Search Algorithm (HSA) as a metaheuristic optimization technique, which operates by simulating musical improvisation processes to iteratively refine network configurations and DG placement locations. The algorithm maintains a harmony memory storing potential solutions, with pitch adjustment mechanisms controlling solution diversification.

Sensitivity analysis techniques are integrated into the framework to quantitatively assess node criticality, typically through power-loss sensitivity indices calculated via partial derivatives of power loss equations with respect to nodal power injections. This analytical layer identifies priority nodes for DG installation by evaluating voltage stability margins and loss reduction potentials. The optimization process incorporates operational constraints including voltage magnitude limits (typically 0.95-1.05 p.u.) and thermal capacity boundaries of distribution branches, formulated as penalty functions within the objective function evaluation.

Validation involves comprehensive testing on standard 33-bus and 69-bus radial distribution networks across light, normal, and peak loading conditions. Performance metrics analyze power loss reduction percentages, voltage deviation indices, and computational efficiency. Results demonstrate significant improvements in both technical and economic indicators, with sensitivity analysis proving effective in reducing solution search space by approximately 40% while maintaining solution quality. The hybrid HSA-sensitivity approach shows particular strength in handling combinatorial complexity of switch status optimization alongside continuous variables of DG sizing and placement.