From Energy Transition Pathways to Measurement Requirements: A Scenario-Based Study of Low-Voltage Grids

TL;DR

This study assesses how different measurement configurations and equipment quality levels affect low-voltage grid performance amid energy transition pathways, highlighting the importance of transformer instrumentation for grid observability.

Contribution

It links energy transition scenarios with measurement requirements, demonstrating the impact of equipment quality and instrumentation on grid stress and estimation accuracy.

Findings

Transformer overloading causes congestion, not line thermal limits.

Adding transformer measurements significantly reduces voltage estimation errors.

Transformer and feeder measurements meet voltage accuracy targets without customer sensors in urban areas.

Abstract

Increasing penetration of electric vehicles, heat pumps, and rooftop photovoltaics is creating thermal and voltage stress in low-voltage distribution grids. This work links three German energy transition pathways (2025-2045) with state estimation performance requirements, evaluated on two SimBench reference networks across three equipment quality levels (good, medium, poor) and three VDE Forum Netztechnik/Netzbetrieb (VDE FNN) measurement constellations that differ in the availability of transformer and feeder-level instrumentation. Congestion is caused exclusively by transformer overloading and voltage-band violations. No individual line exceeds its thermal rating. Equipment quality is the primary factor: under good equipment, congestion remains nearly absent through 2045 (1/26 scenarios), under medium equipment it emerges from 2035 (10/26), under poor equipment from 2025 (25/26), reaching 208 % peak transformer loading. Without transformer instrumentation, voltage estimation errors remain at 6-35% regardless of smart meter penetration. Adding a single transformer measurement reduces errors by a factor of 3 to 24, achieving median errors below 1.1% under poor equipment. Per-feeder measurements achieve comparable accuracy and outperform the transformer-only configuration under poor equipment in rural networks (0.8% vs. 1.1%). In urban networks under poor and medium equipment, transformer and feeder-level instrumentation meet the VDE FNN voltage accuracy target without requiring customer-side sensors. These findings motivate prioritizing transformer instrumentation as an effective first step for grid observability and supplementing the current consumption-driven metering rollout with risk-based deployment criteria linked to local congestion exposure.