Fundamental Frequency Estimation in Power System through the Utilization of Sliding Window-LMS Method

Frequency estimation is a vital tool for many power system applications such as load
shedding, power system security assessment and power quality monitoring. Moreover, the
complexity and noisiness of modern power system networks have created challenges for many power
system applications. Fast and accurate frequency estimation in the presence of noise is a challenging
task. Sliding window with the complex form of least mean square (LMS) algorithm has been utilized
in this study in order to improve the frequency estimation in noisy power system. Different simulation
cases have been examined for signal with different signal to noise ratio (SNR) and to evaluate the
performance of sliding window method for better frequency estimation. The results obtained show
that the sliding window method with LMS is able to improve and enhance the frequency estimation
even when the (SNR) is small compared to the existing LMS method.