Computational Analysis of Impedance Transformations for Four-Wire Power Networks with Sparse Neutral Grounding

TL;DR

This paper introduces a new impedance transformation technique that reduces computational complexity in low-voltage power networks with sparse neutral grounding, enabling faster optimization without significant accuracy loss.

Contribution

The paper presents a novel phase-to-neutral transformation that simplifies power flow models in low-voltage networks with sparse neutral grounding, improving scalability and computational efficiency.

Findings

High accuracy for single-grounded configurations

Provides a 1.42x speed-up in unbalanced power flow optimization

Validated using OpenDSS and PowerModelsDistribution.jl

Abstract

In low-voltage distribution networks, the integration of novel energy technologies can be accelerated through advanced optimization-based analytics such as network state estimation and network-constrained dispatch engines for distributed energy resources. The scalability of distribution network optimization models is challenging due to phase unbalance and neutral voltage rise effects necessitating the use of 4 times as many voltage variables per bus than in transmission systems. This paper proposes a novel technique to limit this to a factor 3, exploiting common physical features of low-voltage networks specifically, where neutral grounding is sparse, as it is in many parts of the world. We validate the proposed approach in OpenDSS, by translating a number of published test cases to the reduced form, and observe that the proposed "phase-to-neutral" transformation is highly accurate for the common single-grounded low-voltage network configuration, and provides a high-quality approximation for other configurations. We finally provide numerical results for unbalanced power flow optimization problems using PowerModelsDistribution.jl, to illustrate the computational speed benefits of a factor of about 1.42.