Optimal Loss Reduction in Distribution Networks Using Conservation Voltage Reduction and Network Topology Reconfiguration

TL;DR

This paper introduces a coordinated optimization framework combining conservation voltage reduction and network topology reconfiguration to significantly reduce power losses in distribution networks.

Contribution

It presents a novel mixed-integer conic programming model that integrates CVR and NTR for improved operational efficiency in radial distribution systems.

Findings

Achieves up to 20.6% reduction in active power losses.

Outperforms independent strategies in simulations.

Maintains voltage compliance and improves load distribution.

Abstract

Conservation voltage reduction (CVR) and network topology reconfiguration (NTR) are widely employed to improve distribution system performance; however, existing approaches largely treat them independently, overlooking their coupled impact on load demand, voltage profiles, and power flow distribution, thereby limiting their overall effectiveness. This paper proposes a coordinated optimization framework for day-ahead operational planning of distribution networks, integrating CVR and NTR to enhance overall network efficiency and reduce active power losses in radial distribution networks. The problem is formulated as a mixed-integer conic programming model incorporating AC power flow constraints, voltage-dependent load representation, and radiality constraints. CVR is implemented to achieve load reduction through coordinated voltage control, while NTR redistributes line loading via optimal switching of controllable branches. The proposed framework is validated on the IEEE 33 and 123-bus distribution systems under varying load conditions. Results demonstrate that the coordinated approach consistently outperforms independent strategies, achieving up to 20.6% reduction in active power losses while maintaining voltage compliance and improving branch loading uniformity. These findings confirm that coordinated optimization provides an effective and scalable solution for enhancing efficiency in modern distribution networks.