Power System Frequency Estimation using Least Mean Square Filter based Algorithm
Bibhu Prasad Ganthia1, Rosalin Pradhan2, Priya Pritam Panda3, Subrat Kumar Barik4

1Bibhu Prasad Ganthia, PhD Research Scholar, School of Electrical Engineering, KIIT University, Bhubaneswar, Odisha, India.
2Rosalin Pradhan, Assistant Professor, Department of Electrical Engineering, IGIT, Sarang, Dhenkanal, Odisha, India.
3Priya Pritam Panda, Assistant Professor, Department of Electrical Engineering, IGIT, Sarang, Dhenkanal, Odisha, India.
4Dr. Subrat Kumar Barik, Associate Professor, School of Electrical Engineering, KIIT University, Bhubaneswar, Odisha, India.

Manuscript received on 29 August 2019. | Revised Manuscript received on 22 September 2019. | Manuscript published on 30 September 2019. | PP: 490-494 | Volume-8 Issue-11, September 2019. | Retrieval Number: K14150981119/2019©BEIESP | DOI: 10.35940/ijitee.K1415.0981119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In the field of electrical power sector frequency as a parameter plays an important role. The value of frequency is not constant, varies according to the load conditions. The power system functionalities like operation, monitoring and controlling of electric device are having lots of contribution to it. So it is required to measure the accurate value of this slowly varying frequency. The total power generated by generating stations is equal to the power consumed and losses under steady state conditions. Due to sudden mismatch in the appearance of generation and load can deviate the frequency from its nominal value. Frequency is an important parameter which influences functions of different relays. This study was performed to calculate the frequency of voltage or current signal in the presence of noise and distortion. In this paper Least Mean Square (LMS) Filter is studied and its frequency estimations are discussed.
Keywords: Adaptive Filters, LMS, RLS, DFT, Frequency Estimation.
Scope of the Article: