Power System Frequency Estimation U Sing the Kernel Least Mean Square Algorithm and the Clarke Transform

摘要

In this work, we propose a methodology for frequency estimation of three-phase power systems using adaptive filtering based on the Kernel Least Mean Square algorithm (KLMS) in the complex form. Generally, abnormal data obtained from measurements may cause noises and affect the accuracy of frequency estimation in a power system. Thus, the proposed method is employed to suppress the abnormal data of measurements allowing greater efficiency in frequency estimation. Results of frequency estimation for distorted signals using the proposed method are compared with LMS algorithms presented in the current literature.