Methods and systems for detection and notification of power outages and power quality

1. A system for detection and notification of electrical power outages, the system comprising:

a sensor device coupled to a circuit, the sensor device configured to

periodically transmit a keepalive packet to a server computing device;

detect an input signal generated by electrical activity on the circuit;

generate an output signal based upon the detected input signal;

monitor the generated output signal during each of a plurality of clock cycles having a predefined duration;

during each clock cycle:

determine whether a rising edge occurred in the generated output signal;

transmit a fault packet to the server computing device when the rising edge occurred prior to a predetermined clock value in the clock cycle or when no rising edge occurred in the clock cycle; and

initiate a new clock cycle;

a server computing device communicably coupled to the sensor device, the server computing device configured to:

receive the fault packet from the sensor device;

listen for one or more keepalive packets from the sensor device;

transmit a power outage notification to one or more remote computing devices when no keepalive packets are received from the sensor device for at least a defined time period after the fault packet is received; and

transmit a power restoration notification to the one or more remote computing devices when one or more keepalive packets are subsequently received from the sensor device after the power outage notification is transmitted.

2. The system of claim 1 , wherein the input signal comprises an alternating current (AC) voltage sine wave with a plurality of zero crossings.

3. The system of claim 2 , wherein the output signal is a voltage curve having a plurality of rising edges corresponding to the zero crossings of the input signal.

4. The system of claim 2 , wherein the keepalive packet comprises power quality data including one or more of: root mean square (RMS) voltage, frequency of the voltage sine wave, relative phase angle of the voltage sine wave, amplitude of the voltage sine wave harmonics, or any number of measures of high frequency noise amplitude.

5. The system of claim 1 , wherein each clock cycle has a predefined duration of 9 milliseconds.

6. The system of claim 5 , wherein the predetermined clock value in the clock cycle is 8.33 milliseconds.

7. A computerized method of detection and notification of electrical power outages, the method comprising:

periodically transmitting, by a sensor device coupled to a circuit, a keepalive packet to a server computing device;

detecting, by the sensor device, an input signal generated by electrical activity on the circuit;

generating, by the sensor device, an output signal based upon the detected input signal;

monitoring, by the sensor device, the generated output signal during each of a plurality of clock cycles having a predefined duration;

during each clock cycle:

determining, by the sensor device, whether a rising edge occurred in the generated output signal;

transmitting, by the sensor device, a fault packet to the server computing device when the rising edge occurred prior to a predetermined clock value in the clock cycle or when no rising edge occurred in the clock cycle;

initiating, by the sensor device, a new clock cycle;

receiving, by the server computing device, the fault packet from the sensor device;

listening for, by the server computing device, one or more keepalive packets from the sensor device;

transmitting, by the server computing device, a power outage notification to one or more remote computing devices when no keepalive packets are received from the sensor device for at least a defined time period after the fault packet is received; and

transmitting, by the server computing device, a power restoration notification to the one or more remote computing devices when one or more keepalive packets are subsequently received from the sensor device after the power outage notification is transmitted.

8. The method of claim 7 , wherein the input signal comprises an alternating current (AC) voltage sine wave with a plurality of zero crossings.

9. The method of claim 8 , wherein the output signal is a voltage curve having a plurality of rising edges corresponding to the zero crossings of the input signal.

10. The method of claim 8 , wherein the keepalive packet comprises power quality data including one or more of: root mean square (RMS) voltage, frequency of the voltage sine wave, relative phase angle of the voltage sine wave, amplitude of the voltage sine wave harmonics, or any number of measures of high frequency noise amplitude.

11. The method of claim 7 , wherein each clock cycle has a predefined duration of 9 milliseconds.

12. The method of claim 11 , wherein the predetermined clock value in the clock cycle is 8.33 milliseconds.

13. A system for detection and notification of electrical power quality, the system comprising:

one or more sensor devices each coupled to a circuit, each sensor device configured to

detect an input signal generated by electrical activity on the circuit;

generate an output signal based upon the detected input signal; and

transmit power quality data to a server computing device, the power quality data based upon the output signal;

the server computing device configured to

receive the power quality data from the one or more sensor devices;

analyze the power quality data in conjunction with historical power quality data received from the one or more sensor devices to detect one or more power quality events;

and

transmit a power quality notification to one or more remote computing devices based upon the detected power quality events.

14. The system of claim 13 , wherein the detected one or more power quality events comprise one or more of: surge events, surge jump events, sag events, sag jump events, brownout events, swell jump events, high frequency (HF) filter jump events, frequency jump events, recurring power quality problems, phase angle jump events, loose neutral events, or generator activation events.

15. The system of claim 14 , wherein the server computing device is further configured to correlate (i) the detected one or more power quality events with zero or more external events and/or (ii) a detected power quality event from a first sensor device with a detected power quality event from one or more other sensor devices.

16. The system of claim 15 , wherein the server computing device detects a loose neutral event by:

analyzing, for a single sensor device, a number and amplitude of surge events, surge jump events, and sag events recorded by the single sensor device within a predetermined time period which do not correlate with matching power quality events from any other sensor devices in proximity to the single sensor device; and

generating a loose neutral event when an average number of the surge events is greater than a first defined number per day, or an average number of the surge jump events having a magnitude greater than a defined percentage of a nominal voltage is greater than a second defined number per day, or an average number of the sag events is greater than a third defined number per day.

17. The system of claim 15 , wherein the output signal comprises one or more of: root mean square (RMS) voltage, frequency of the voltage sine wave, relative phase angle of the voltage sine wave, amplitude of the voltage sine wave harmonics, or any number of measures of high frequency noise amplitude.

18. The system of claim 17 , wherein the server computing device detects a surge event by:

analyzing a plurality of sequential data points of RMS voltage from one or more sensor devices;

and

generating a surge event when the RMS voltage is greater than a predefined threshold percentage of a nominal voltage for a number of consecutive data points.

19. The system of claim 18 , wherein the predefined threshold percentage varies based upon the number of consecutive data points in which the RMS voltage is greater than a minimum threshold percentage.

20. The system of claim 15 , wherein the server computing device detects a brownout event by:

analyzing a plurality of sequential data points of RMS voltage from one or more sensor devices;

and

generating a brownout event when the RMS voltage is less than a predefined threshold percentage of a nominal voltage for a number of consecutive data points.

21. The system of claim 20 , wherein the predefined threshold percentage varies based upon the number of consecutive data points in which the RMS voltage is less than a minimum threshold percentage.

22. The system of claim 15 , wherein the server computing device detects a sag jump event by:

analyzing a plurality of sequential data points of RMS voltage from one or more sensor devices;

and

generating a sag jump event for each of one or more drops of RMS voltage that occurred in the plurality of sequential data points and that are larger than a predefined threshold percentage of a nominal voltage.

23. The system of claim 15 , wherein the server computing device detects a swell jump event by:

analyzing a plurality of sequential data points of RMS voltage from one or more sensor devices;

and

generating a swell jump event for each of one or more increases of RMS voltage that occurred in the plurality of sequential data points and that are larger than a predefined threshold percentage of a nominal voltage.

24. The system of claim 15 , wherein the server computing device detects a HF Filter jump event by:

analyzing a plurality of sequential data points of HF amplitude data from one or more sensor devices;

calculating a mean of the HF amplitude data; and

when the mean is greater than one, generating an HF Filter jump event when the HF amplitude data increases by more than a threshold multiple of the mean, or

when the mean is less than one, generating an HF Filter jump event when the HF amplitude data increases above a predefined threshold.

25. The system of claim 15 , wherein the server computing device detects a frequency jump event by:

analyzing a plurality of sequential data points of frequency data from one or more sensor devices;

calculating an average of the frequency data;

calculating a standard deviation of the frequency data; and

generating a frequency jump event when the frequency increases by more than a predefined threshold from the average, or

generating a frequency jump event when (i) the standard deviation changes from less than a first frequency to greater than a second frequency or (ii) the standard deviation changes from greater than the second frequency to less than the first frequency.

26. The system of claim 15 , wherein the server computing device detects a generator activation event by:

analyzing, for a single sensor device, whether any power outage events and frequency events were detected by the single sensor device during a predetermined time period; and

generating a generator activation event when the single sensor device detected a power outage event followed by a frequency standard deviation change to greater than a predefined threshold within a predefined period of time of the power outage event and the frequency standard deviation change was not associated with a correlated external event.

27. The system of claim 15 , wherein the one or more external events comprise lightning activity events, electrical grid monitoring events, and energy pricing events.

28. The system of claim 15 , wherein the detected power quality event from the first sensor device and the detected power quality event from one or more other sensor devices are of a same event type.

29. A computerized method of detection and notification of electrical power quality, the system comprising:

detecting, by a sensor device coupled to a circuit, an input signal generated by electrical activity on the circuit;

generating, by the sensor device, an output signal based upon the detected input signal;

transmitting, by the sensor device, power quality data to a server computing device, the power quality data based upon the output signal;

receiving, by the server computing device, the power quality data from the sensor device;

analyzing, by the server computing device, the power quality data in conjunction with historical power quality data received from the sensor device to detect one or more power quality events; and

transmitting, by the server computing device, a power quality notification to one or more remote computing devices based upon the detected power quality events.

30. The method of claim 29 , wherein the detected one or more power quality events comprise one or more of: surge events, surge jump events, sag events, sag jump events, brownout events, swell jump events, high frequency (HF) filter jump events, frequency jump events, recurring power quality problems, phase angle jump events, loose neutral events, or generator activation events.

31. The method of claim 30 , wherein the server computing device further correlates (i) the detected one or more power quality events with zero or more external events and/or (ii) a detected power quality event from a first sensor device with a detected power quality event from one or more other sensor devices.

32. The method of claim 31 , wherein the server computing device detects a loose neutral event by:

analyzing, for a single sensor device, a number and amplitude of surge events, surge jump events, and sag events recorded by the single sensor device within a predetermined time period which do not correlate with matching power quality events from any other sensor devices in proximity to the single sensor device; and

generating a loose neutral event when an average number of the surge events is greater than a first defined number per day, or an average number of the surge jump events having a magnitude greater than a defined percentage of a nominal voltage is greater than a second defined number per day, or an average number of the sag events is greater than a third defined number per day.

33. The method of claim 31 , wherein the output signal comprises one or more of: root mean square (RMS) voltage, frequency of the voltage sine wave, relative phase angle of the voltage sine wave, amplitude of the voltage sine wave harmonics, or any number of measures of high frequency noise amplitude.

34. The method of claim 33 , wherein the server computing device detects a surge event by:

analyzing a plurality of sequential data points of RMS voltage from one or more sensor devices;

and

generating a surge event when the RMS voltage is greater than a predefined threshold percentage of a nominal voltage for a number of consecutive data points.

35. The method of claim 34 , wherein the predefined threshold percentage varies based upon the number of consecutive data points in which the RMS voltage is greater than a minimum threshold percentage.

36. The method of claim 33 , wherein the server computing device detects a brownout event by:

analyzing a plurality of sequential data points of RMS voltage from one or more sensor devices;

and

generating a brownout event when the RMS voltage is less than a predefined threshold percentage of a nominal voltage for a number of consecutive data points.

37. The method of claim 36 , wherein the predefined threshold percentage varies based upon the number of consecutive data points in which the RMS voltage is less than a minimum threshold percentage.

38. The method of claim 33 , wherein the server computing device detects a sag jump event by:

analyzing a plurality of sequential data points of RMS voltage from one or more sensor devices;

and

generating a sag jump event for each of one or more drops of RMS voltage that occurred in the plurality of sequential data points and that are larger than a predefined threshold percentage of a nominal voltage.

39. The method of claim 33 , wherein the server computing device detects a swell jump event by:

analyzing a plurality of sequential data points of RMS voltage from one or more sensor devices;

and

generating a swell jump event for each of one or more increases of RMS voltage that occurred in the plurality of sequential data points and that are larger than a predefined threshold percentage of a nominal voltage.

40. The method of claim 33 , wherein the server computing device detects a HF Filter jump event by:

analyzing a plurality of sequential data points of HF amplitude data from one or more sensor devices;

calculating a mean of the HF amplitude data; and

when the mean is greater than one, generating an HF Filter jump event when the HF amplitude data increases by more than a threshold multiple of the mean, or

when the mean is less than one, generating an HF Filter jump event when the HF amplitude data increases above a predefined threshold.

41. The method of claim 33 , wherein the server computing device detects a frequency jump event by:

analyzing a plurality of sequential data points of frequency data from one or more sensor devices;

calculating an average of the frequency data;

calculating a standard deviation of the frequency data; and

generating a frequency jump event when the frequency increases by more than a predefined threshold from the average, or

generating a frequency jump event when (i) the standard deviation changes from less than a first frequency to greater than a second frequency or (ii) the standard deviation changes from greater than the second frequency to less than the first frequency.

42. The method of claim 33 , wherein the server computing device detects a generator activation event by:

analyzing, for a single sensor device, whether any power outage events and frequency events were detected by the single sensor device during a predetermined time period; and

generating a generator activation event when the single sensor device detected a power outage event followed by a frequency standard deviation change to greater than a predefined threshold within a predefined period of time of the power outage event and the frequency standard deviation change was not associated with a correlated external event.

43. The method of claim 33 , wherein the one or more external events comprise lightning activity events, electrical grid monitoring events, and energy pricing events.

44. The method of claim 33 , wherein the detected power quality event from the first sensor device and the detected power quality event from one or more other sensor devices are of a same event type.