Limitations in the Use of R.M.S. Value in Power Quality Analysis

Barros,; Perez, Claudio A.

doi:10.1109/imtc.2006.328575

Cited by 21 publications

(7 citation statements)

References 3 publications

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“…[3], the error in the computation of the magnitude of short duration voltage dips using the U rms(1/2) method can be of such a magnitude that the voltage dip might go undetected, because under these conditions the detection threshold might not be surpassed. However, voltage dips of Table 2 Maximum error in the magnitude of voltage dips of 0.5, 0.75 and 1 cycles using the U rms (1/2) any magnitude, duration and point-on-the-wave of beginning are always detected using the EKF method proposed.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…The U rms(1/2) method is simple and easy to implement, but shows a limited performance in the detection and in the estimation of magnitude and duration, mainly for short duration and less severe voltage dips [3]. Using the U rms(1/2) value, the magnitude of a voltage dip is exactly computed only when the duration of the voltage dip is greater than the sampling window used.…”

Section: Introductionmentioning

confidence: 99%

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An extended Kalman filtering approach for detection and analysis of voltage dips in power systems

Pérez

Barros

2008

Electric Power Systems Research

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An extended Kalman filtering approach for detection and analysis of voltage dips in power systems

Pérez

Barros

2008

Electric Power Systems Research

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“…The synchronization of sampling to the power frequency is not necessary, as the difference between synchronized and non-synchronized rms measurements is small [2]. On the other hand, determination of the start and end instants is inaccurate, as the rms voltage may take up to one cycle to transition from the pre-event to the duringevent values [5]. Reference [6] proposes to reduce the sliding window length to half-cycle to improve the accuracy; its main advantage is a faster transition between steady-state and sag/swell voltage values.…”

Section: A Estimation Methods Using Threshold Rms Voltagementioning

confidence: 99%

Comparison of Methods for Determining Inception and Recovery Points of Voltage Variation Events

Bastos

Santoso

Todeschini

2018

2018 IEEE Power &Amp; Energy Society General Meeting (PESGM)

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Voltage sags and swells occur often in power systems; however determining the duration of these events is not straightforward. Seven methods for estimating the inception and recovery points (and consequently, the duration) of voltage sags and swells are surveyed: threshold rms voltage, waveform envelope, discrete wavelet transform, missing voltage, dq transformation, numerical matrix, and peak detector. Each method has its own strengths and weaknesses; however, no one method works on all conditions. An algorithmic approach to determining inception and recovery points is suggested. Such approach employs one method in combination with other methods based on the event characteristics.

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“…On the one hand, the RMS method is simple, well known, and easy to implement. On the other hand, the limitations in the use of RMS values in power quality analysis from the point of view of the IEC standard have been clearly overviewed [21,22]. In a single-phase, the major drawbacks that affect both the performance feasibility and the accuracy of results are:…”

Section: Discrete Rms Value Determinationmentioning

confidence: 99%

“…To perform this experiment, a general purpose ATmega328P microcontroller-based prototype, as given in [22], was built and configured with a clock frequency of 16 MHz. The selected sampling frequency was 1 kHz, i.e., a 20 samples per AC voltage signal period, and the programmed procedure fit what is described in Figure 1 and in Equation 3.…”

Section: Contrast Experiment: Expanding the Samples Vector And Employmentioning

confidence: 99%

A Memory-Efficient True-RMS Estimator in a Limited-Resources Hardware

et al. 2019

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More and more human activities are increasingly dependent on the power quality energy they are supplied. In particular, those loads that have an electronic switching mode power supply (SMPS) and microcontrollers or microprocessors are very susceptible to de-energization of the AC line as voltage monitoring takes place on the DC end and may not have enough time to cope with a voltage event involving energy loss. There have been many proposals that analyze power quality or current consumption, even those using limited resources hardware or the classic formulas of discrete root mean square (RMS). In this proposal, an approximation to the problem by means of an RMS value estimator that uses as a base a microcontroller of basic range and low economic cost and algorithms of calculation of very low computational cost that elude complex arithmetic operation to controllers, such as powers or roots, is presented. The results of the experiments to which the proposal was subjected show its ability to provide an estimation of the RMS value of voltage with sufficient precision or an event alarm in less time than the options analyzed. The validation tests and functional comparison of the prototype which were carried out support its viability.

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Limitations in the Use of R.M.S. Value in Power Quality Analysis

Cited by 21 publications

References 3 publications

An extended Kalman filtering approach for detection and analysis of voltage dips in power systems

An extended Kalman filtering approach for detection and analysis of voltage dips in power systems

Comparison of Methods for Determining Inception and Recovery Points of Voltage Variation Events

A Memory-Efficient True-RMS Estimator in a Limited-Resources Hardware

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