2015Unpublished venueOpen access

Adjustable window for amplitude estimation considering the time-varying frequency of power systems signals

Thiago R. F. Mendonca, Milena F. Pinto, Carlos A. Duque

Open full text 1 citations

Abstract

The development of signal processing techniques that allows the estimation of parameters from the power system are crucial to keep the grid within a safe margin of operation. Some methods require a specific sampling rate in order to avoid asynchronous sampling, which may result in errors in estimation algorithms. Due to unbalances between demand and supply, the power signal is time-varying in nature, hindering the selection of an optimal fixed window length. In this work is proposed a technique in which the window length adapts to the actual value of estimated frequency, achieving better performance. The filter utilized to test the method was a moving average filter, but it can be expanded for other algorithms. Results have shown good performance when changing the filter coefficients according to frequency estimation.

Open-access reader

About this research paper

What this paper is about

The development of signal processing techniques that allows the estimation of parameters from the power system are crucial to keep the grid within a safe margin of operation. Some methods require a specific sampling rate in order to avoid asynchronous sampling, which may result in errors in estimation algorithms. Due to unbalances between demand and supply, the power signal is time-varying in nature, hindering the selection of an optimal fixed window length. In this work is proposed a technique in which the window length adapts to the actual value of estimated frequency, achieving better performance. The filter utilized to test the method was a moving average filter, but it can be expanded for other algorithms. Results have shown good performance when changing the filter coefficients according to frequency estimation.

Why it matters

OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

The development of signal processing techniques that allows the estimation of parameters from the power system are crucial to keep the grid within a safe margin of operation. Some methods require a specific sampling rate in order to avoid asynchronous sampling, which may result in errors in estimation algorithms. Due to unbalances between demand and supply, the power signal is time-varying in nature, hindering the selection of an optimal fixed window length. In this work is proposed a technique in which the window length adapts to the actual value of estimated frequency, achieving better performance. The filter utilized to test the method was a moving average filter, but it can be expanded for other algorithms. Results have shown good performance when changing the filter coefficients according to frequency estimation.

Key concepts: Computer science, Filter (signal processing), Window (computing), Sampling (signal processing), Power (physics), Control theory (sociology), Asynchronous communication, Margin (machine learning)

Related papers

Back to paper searchBrowse research topicsOriginal source
Adjustable window for amplitude estimation considering the time-varying frequency of power systems signals — Research Paper | ScholarLens