Power Distribution Network Reconfiguration for Distributed Generation Maximization

TL;DR

This paper introduces an exact, reliable method for reconfiguring power distribution networks to maximize distributed generation capacity, overcoming limitations of previous relaxation-based approaches.

Contribution

It proposes a bilinear programming framework with spatial branch-and-bound to accurately optimize network topology and power dispatch in real-time.

Findings

The method reliably performs reconfiguration and dispatch within real-time constraints.

Counterexamples show relaxations can produce erroneous results.

Numerical studies validate the approach on benchmark and real-world systems.

Abstract

Network reconfiguration can significantly increase the hosting capacity (HC) for distributed generation (DG) in radially operated systems, thereby reducing the need for costly infrastructure upgrades. However, when the objective is DG maximization, jointly optimizing topology and power dispatch remains computationally challenging. Existing approaches often rely on relaxations or approximations, yet we provide counterexamples showing that interior point methods, linearized DistFlow and second-order cone relaxations all yield erroneous results. To overcome this, we propose a solution framework based on the exact DistFlow equations, formulated as a bilinear program and solved using spatial branch-and-bound (SBB). Numerical studies on standard benchmarks and a 533-bus real-world system demonstrate that our proposed method reliably performs reconfiguration and dispatch within time frames compatible with real-time operation.