2016/03/08 by Sayed Pouria Talebi, Talebi, Sayed Pouria, Danilo P. Mandic +1
Engineering · Mathematics · #Advanced Adaptive Filtering Techniques #Applications (stat.AP) #FOS: Computer and information sciences #Machine Learning (stat.ML) #Power Quality and Harmonics #Power System Optimization and Stability #stat.AP #stat.ML
paper · pdf · doi:10.48550/arxiv.1603.02977
arxiv created 2016/03/08 · openalex publication_date 2016/03/08 · arxiv updated 2016/03/10 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28
Motivated by the need for accurate frequency information, a novel algorithm for estimating the fundamental frequency and its rate of change in three-phase power systems is developed. This is achieved through two stages of Kalman filtering. In the first stage a quaternion extended Kalman filter, which provides a unified framework for joint modeling of voltage measurements from all the phases, is used to estimate the instantaneous phase increment of the three-phase voltages. The phase increment estimates are then used as observations of the extended Kalman filter in the second stage that accounts for the dynamic behavior of the system frequency and simultaneously estimates the fundamental frequency and its rate of change. The framework is then extended to account for the presence of harmonics. Finally, the concept is validated through simulation on both synthetic and real-world data.