Novel Moving Average Filter for Detecting RMS Voltage Step Changes in Triggerless PQ Data

Abstract

The voluminous amount of raw waveform data recorded by triggerless power quality monitors contain conspicuous and inconspicuous disturbance events. Data reduction and detection techniques are needed to efficiently extract useful information hidden in the raw data and identify power quality disturbances. The overall objective of this study is to use step changes in the rms voltage profile as an alternative triggering feature for automatically detecting switching events. The full characterization of the event is based on processing a small portion of the voltage waveform selected around the detected rms voltage step change. A filtering method is proposed to smooth out rapid fluctuations in the rms voltage profile during steady-state operation, while preserving the sharp edges caused by rms voltage step changes. Once the rms voltage profile has been filtered, adaptive limits based on the median absolute deviation are computed for detecting rms voltage step changes. The effectiveness of the proposed technique is evaluated using triggerless voltage waveforms to detect capacitor switching events. The use of the filtered rms voltage profile allows accurate detection of capacitor energizing and de-energizing events, while more than 50% of the detections in the unfiltered profile correspond to false-positives.

Detection of inconspicuous power quality disturbances through step changes in rms voltage profile

“…A previous study employed the same unfiltered rms voltage profile depicted in Fig. 10 a to detect subtle rms voltage step changes [33]. The method proposed in the previous study and the current approach has the same performance, i.e.…”

“…Regarding the statistical tests described in the previous study, the user is required to set a significance level; a value of 5% was chosen in [33]. This value has no physical meaning, so that extensive prior analysis may be necessary for determining it.…”

“…For a univariate dataset , is defined as where b is a scale factor needed for making a consistent estimator of the parameter of interest [42] (this factor depends on the underlying distribution). A previous study indicates that it is reasonable to assume that the rms voltage profile converges to a normal distribution during quasi‐steady‐state conditions [33]; in such a case, .…”

“…More precisely, when a moving average filter with length M is applied around an rms voltage step change, the filtered rms voltage profile gradually changes from the pre‐step to the post‐step voltage levels. This transition introduces intermediary points between the two steady‐state conditions [33].…”

An Automated Technique for Extracting Phasors from Protective Relay’s Event Reports

“…or corresponding voltage quantities as two sets of data as proposed in [28], cannot be performed because the sets of data used for analysis must correspond to a normal distribution. This assumption that portions of the rms current and rms voltage profiles will belong to a normal distribution cannot be made, especially during a fault event where there are step changes in the values.…”