$\alpha \alpha \beta$-Based Fast and Accurate Frequency and ROCOF Measurement in Power Systems

The frequency and rate of change of frequency (ROCOF) signals acquired from phasor measurement units (PMUs) are instrumental in the security monitoring and feedback control of power grids, necessitating minimal response time and high precision. Existing algorithms rarely achieve a simultaneous balance between superior noise filtering performance and rapid response time when measuring frequency and ROCOF. To address this problem, this article introduces an innovative algorithm that integrates <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\alpha \beta \gamma$</tex-math></inline-formula> series filters. The proposed algorithm leverages an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\alpha \alpha \beta$</tex-math></inline-formula> (aab) filter, which combines an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\alpha$</tex-math></inline-formula> filter and an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\alpha \beta$</tex-math></inline-formula> filter, and the reference P-class PMU algorithm from the IEC/IEEE 60255.118.1-2018 standard file. By providing an original mathematical modeling approach to aab parameter acquisition, this filter effectively amalgamates the advantages of the two foundational filters. Extensive experimental simulations demonstrate that our proposed algorithm has exceptional performance across various metrics of frequency and ROCOF measurement, achieving results that compare favorably with other advanced algorithms.