Choice and properties of adaptive and tunable digital boxcar (moving average) filters for power systems and other signal processing applications

Roscoe, Andrew; Blair, Steven M.

doi:10.1109/amps.2016.7602853

Cited by 21 publications

(16 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Two PMU implementations have been used to demonstrate the use of the measurement method proposed in this paper: the RTDS GTNET simulated PMU (which is based on the IEEE C37.118.1 reference PMU) and an adaptive filter-based PMU implementation described in [22]- [24]. The results are summarized in Table 2, and are discussed in the following subsections.…”

Section: Pmu Testing Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Measurement and Analysis of PMU Reporting Latency for Smart Grid Protection and Control Applications

Blair¹,

Syed²,

Roscoe

et al. 2019

IEEE Access

Self Cite

View full text Add to dashboard Cite

Emerging power system protection and control applications require faster-responding measurements and more accurate knowledge of the actual latency of the measurement and communications systems. A new method for accurately determining the reporting latency of a phasor measurement unit (PMU) has been developed and demonstrated. This method operates in real-time, works passively for any existing PMU without requiring changes to the PMU hardware or software, and it is very accurate-providing a measurement uncertainty of <500 ns in many cases, significantly surpassing the 0.002 s accuracy requirement in the most recent IEEE Synchrophasor standard. Only low-cost hardware and open source software are required. It is particularly important to understand end-to-end system latency, including the impact of local and wide-area communications, rather than just the latency of the PMU device; the proposed method also supports such practical measurements. It is therefore shown how this advance can be used to enable efficient, but realistic, cross-domain power system simulation studies, which incorporate measurement and communications delays. These capabilities address complexity and uncertainty in the design and operation of future PMU-based protection and control functions for new smart grid services.

show abstract

Section: Pmu Testing Resultsmentioning

confidence: 99%

“…The adaptive filter PMU algorithm is based on the Discrete Fourier Transform with adaptive filtering and other enhancements as described in [22]- [24]. The algorithm has been implemented on a Beckhoff hardware platform which provides time synchronization using PTP [25].…”

Section: ) Adaptive Filter Pmu Implementation Resultsmentioning

confidence: 99%

Measurement and Analysis of PMU Reporting Latency for Smart Grid Protection and Control Applications

Blair¹,

Syed²,

Roscoe

et al. 2019

IEEE Access

Self Cite

View full text Add to dashboard Cite

show abstract

“…1, is installed at the LV-Bus. Details concerning the design of the PMU can be found in [24] and [25]. Additionally, using the GTNET-PMU firmware of the DRTS, eight more P class PMUs [26] are represented.…”

Section: Power Hardware-in-the-loop Setup a System Under Studymentioning

confidence: 99%

Power Hardware-in-the-Loop Setup for Developing, Analyzing and Testing Mode Identification Techniques and Dynamic Equivalent Models

Kontis

Nousdilis

Papagiannis

et al. 2019

2019 IEEE Milan PowerTech

View full text Add to dashboard Cite

During the last decades, a significant number of mode identification techniques and dynamic equivalent models have been proposed in the literature to analyze the dynamic properties of transmission grids and active distribution networks (ADNs). The majority of these methods are developed using the measurement-based approach, i.e., by exploiting dynamic responses acquired from phasor measurement units (PMUs). However, there is lack of a common framework in the literature for the performance evaluation of such methods under real field conditions. Aiming to address this gap, in this paper, a power hardware-in-the-loop setup is introduced to generate dynamic responses, suitable for the testing and validation of measurementbased mode identification techniques and dynamic equivalent models. The setup consists of a high voltage transmission grid, two medium voltage distribution grids as well as a low voltage ADN. Using this setup, several disturbances are emulated and the resulting dynamic responses are recorded using PMUs. The measurements are made available to other researchers through a public repository to act as benchmark responses for the evaluation of measurement-based methods.

show abstract

“…Some of the concepts were laid down in [7], although the method we use is unconditionally (not marginally) stable, allows the use of windows that are non-integer numbers of samples, and allows the use of floating-point arithmetic without overflow or loss of precision. The method used is described in [8][9][10] and operates extremely quickly in real-time [11]. To include the adaptive tuning of fT to the measured value of fC in Fig.…”

Section:    mentioning

confidence: 99%

Dealing With Front-End White Noise on Differentiated Measurements Such as Frequency and ROCOF in Power Systems

Roscoe

Blair

Dickerson³

et al. 2018

IEEE Trans. Instrum. Meas.

Self Cite

View full text Add to dashboard Cite

This paper describes the way that white noise (including quantised input section sampling) imparts errors onto frequency and rate-of-change-of-frequency (ROCOF) measurements. The main paper focus concerns the use of filtered heterodyned (i.e. Fourier) analyses for single-phase and 3-phase systems, and the filtered Clarke transform for 3-phase systems. The rules and equations governing the effect of white noise on frequency and ROCOF are formulated for these techniques, explaining the subtle effects of aliasing, splitting signals and noise into their positive and negative frequency components, and the correlation or de-correlation of noise. It is shown that-as expected-for 3phase AC measurements, averaging 3 single-phase Fourier measurements produces the same performance against noise as using a method based on Clarke's transform, if identical filtering is used. Furthermore, by understanding the theory behind the frequency and ROCOF measurement processes, it is shown that to achieve the lowest RMS errors, in the presence of front-end white noise (alone, ignoring other dynamic signal and power quality aspects), a filter which provides ~40 dB/decade attenuation (i.e. a 2-boxcar cascade) is recommended for a frequency measurement, but a filter which rolls off at ~60 dB/decade (i.e. a 3-boxcar cascade) is recommended for a ROCOF measurement. 

show abstract

Choice and properties of adaptive and tunable digital boxcar (moving average) filters for power systems and other signal processing applications

Cited by 21 publications

References 12 publications

Measurement and Analysis of PMU Reporting Latency for Smart Grid Protection and Control Applications

Measurement and Analysis of PMU Reporting Latency for Smart Grid Protection and Control Applications

Power Hardware-in-the-Loop Setup for Developing, Analyzing and Testing Mode Identification Techniques and Dynamic Equivalent Models

Dealing With Front-End White Noise on Differentiated Measurements Such as Frequency and ROCOF in Power Systems

Contact Info

Product

Resources

About