# Experimental Validation of Simple Power Quality Indices for Frequency Content Assessment up to 150 kHz

## TL;DR

This paper introduces new power quality indices to help identify electrical issues in modern power systems, validated across a wide frequency range.

## Contribution

The paper proposes and validates new PQ indices that are flexible and effective for assessing power quality across diverse frequencies.

## Key findings

- New PQ indices were validated on synthetic and real signals, showing effectiveness in identifying power quality issues.
- The indices work well across a wide frequency range (50 Hz–150 kHz) and can be combined with existing metrics for better classification.
- A case study demonstrated practical application and promising results in real-world power networks.

## Abstract

The power system is evolving with the integration of new technologies, including electronic devices and renewable energy sources, which are increasingly used to support new applications, reduce dependence on fossil fuels, and drive system innovation. However, this shift brings a significant drawback: a reduction in power quality (PQ). The literature extensively discusses the impact of poor PQ on electrical assets and explores potential solutions to this new challenge. Building on this foundation, this paper introduces new PQ indices derived from existing metrics and validated on both synthetic and real signals to assess their effectiveness. The aim is to provide researchers and system operators with simple and efficient tools for the clear identification of PQ issues in monitored networks. These new indices are designed to be flexible and independent of acquisition conditions, making them suitable for a wide range of frequencies (e.g., 50 Hz–150 kHz) and applications. After an overview of the PQ landscape, the paper demonstrates the use of these indices on various voltage waveforms, including a case study from a measurement campaign. The promising results indicate that, when combined with existing indices, these new metrics can form a strong foundation for a deeper understanding and more accurate classification of PQ issues in power networks.