Experimental Evaluation and Systematic-Error Reduction of Frequency Estimation Using the Zero-Crossing Technique for Dynamic Power Grids

Abstract

Fundamental frequency estimates are essential for control and monitoring purposes in power systems. Hence, many devices exist that report frequency values. Future power system dynamics call for accurate frequency estimates with high reporting rates and a detailed determination of the measurement uncertainty. For a sophisticated analysis, even the used estimation algorithm becomes increasingly important in order to interpret the results. In this context, we present the evaluation of the well-known zero-crossing technique. We apply dedicated test signals in a hardware-based measurement setup and determine the resulting error metrics. We highlight the importance of differentiating between steady-state and dynamic test conditions, propose steps for an enhanced error assessment, and suggest possible ways to reduce systematic errors. We successfully implement an approach to reduce systematic errors under dynamic conditions and thereby significantly improve the comparability of frequency estimates of the zero-crossing algorithm.