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. © (2014) Trans Tech Publications, Switzerland.