System, and method for quantifying voltage anomalies
A system and method of quantifying voltage anomalies may be used to quantify low frequency voltage transients such as the type caused by power factor correction (PFC) or similar events. The system and method of quantifying voltage anomalies receives sampled voltage data values and computes ideal sine wave data values. The system and method of quantifying voltage anomalies may also compute difference data values representing a difference between the received voltage data and the ideal sine wave and may compute score data values such as non-linear score values representing the difference data values relative to a peak voltage value or RMS voltage value.
1. A method of quantifying voltage anomalies to evaluate power quality at a site being monitored, said method comprising:
receiving sampled voltage data representing voltage measured on at least one voltage input at the site being monitored;
computing an ideal sine wave corresponding to said voltage data;
computing a difference between values of said voltage data and values of said ideal sine wave to generate difference values; and
computing score values based on said difference values relative to a reference voltage value associated with said sampled voltage data, wherein said score values include non-linear score values with a non-linear relationship to said reference voltage value, wherein said score values quantify voltage anomalies in said voltage measured on said at least one voltage input at the site being monitored and are indicative of power quality at the site being monitored.
2. The method of claim 1 further comprising:
generating a voltage data plot from said sampled voltage data; and
overlaying said ideal sine wave onto said voltage data plot.
3. The method of claim 1 further comprising monitoring said score values in real time to identify said voltage anomalies.
4. The method of claim 3 further comprising:
comparing said score values to threshold score values to identify a voltage anomaly; and
providing a notification of said identified voltage anomaly.
5. The method of claim 1 wherein said voltage anomalies include low frequency voltage transients.
6. The method of claim 1 wherein said voltage anomalies include a sub-cycle disturbance in a voltage waveform having that has a frequency less than 15 kilohertz.
7. The method of claim 1 wherein said voltage anomalies are caused by power factor correction (PFC).
8. The method of claim 1 further comprising identifying power quality events, wherein said sampled voltage data is associated with said power quality events.
9. The method of claim 8 further comprising:
computing average score values from said score values associated with each of said power quality events and peak score values from said score values associated with each of said power quality events; and
identifying at least one of said power quality events as a voltage anomaly based on said average score values and said peak score values.
10. The method of claim 9 wherein identifying said at least one of said power quality events comprises:
monitoring said average score values and said peak score values in real time;
comparing said score values to threshold score values to identify said voltage anomaly; and
providing a notification of said identified voltage anomaly.
11. The method of claim 9 further comprising generating at least one event report for at least one of said power quality events identified as a voltage anomaly.
12. The method of claim 11 wherein said at least one report includes plots and identifying information.
13. The method of claim 1 wherein said reference voltage value is a peak voltage value or a root mean squared (RMS) voltage value.
14. The method of claim 1 said non-linear score values are determined according to the following equation: Vdiff 3 /Vref 2 , where Vdiff is a difference value and Vref is a RMS voltage value.
15. The method of claim 1 further comprising computing an average score value from said score values.
16. The method of claim 1 further comprising computing a peak score value from said score values.
17. A machine-readable medium whose contents cause a computer system to perform a method for quantifying voltage anomalies to evaluate power quality at a site being monitored, said method comprising:
receiving sampled voltage data representing voltage measured on at least one voltage input at the site being monitored;
computing an ideal sine wave corresponding to said voltage data;
computing a difference between values of said voltage data and values of said ideal sine wave to generate difference values; and
computing score values based on said difference values relative to a reference voltage value associated with said sampled voltage data, wherein said score values include non-linear score values with a non-linear relationship to said reference voltage value, wherein said score values quantify voltage anomalies in said voltage measured on said at least one voltage input at the site being monitored and are indicative of power quality at the site being monitored.
18. The machine readable medium of claim 17 wherein said sampled voltage data is associated with power quality events, and wherein the method further comprises:
computing average score values from said score values associated with each of said power quality events and peak score values from said score values associated with each of said power quality events; and
identifying at least one of said power quality events as a voltage anomaly based on said average score values and said peak score values.
19. The machine readable medium of claim 17 wherein said reference voltage value is a RMS voltage value.
20. A power monitoring system comprising:
at least one analog receiver configured to receive at least one analog voltage measurement at a site being monitored and to convert said analog voltage measurement into sampled voltage data;
at least one data processor coupled to said analog receiver and configured to process said sampled voltage data, wherein said data processor is configured to compute an ideal sine wave corresponding to said sampled voltage data, to compute a difference between values of said voltage data and values of said ideal sine wave to generate difference values, and to compute score values based on said difference values relative to a reference voltage value associated with said sampled voltage data, wherein said score values include non-linear score values with a non-linear relationship to said reference voltage value, wherein said score values quantify voltage anomalies in said voltage measurement at the site being monitored and are indicative of power quality at the site being monitored.
21. The system of claim 20 wherein said score values include non-linear score values with a non-linear relationship to a RMS voltage value computed from said sampled voltage data.