Method and system for detecting and notifying power interruptions and power quality

Abstract

Methods and systems for detecting and notifying power outages and power quality are described herein. A sensor coupled to a circuit transmits keep-alive packets to a server. The sensor detects an input signal generated by electrical activity. The sensor generates an output signal based on the input signal. The sensor monitors the output signal. During a clock cycle, the sensor determines whether a rising edge occurs and transmits a failure packet to the server if a rising edge occurs before a predetermined clock value or if no rising edge occurs. The server receives the failure packet from the sensor and listens for the keep-alive packets. When no keep-alive packets are received within at least a defined period of time after the failure packet is received, the server transmits a power outage notification. When one or more keep-alive packets are subsequently received, the server transmits a power restoration notification.

Description

[0001] Related applications

[0002] This application claims priority to U.S. Provisional Patent Application No. 62 / 989,415, filed March 13, 2020, which is incorporated herein by reference in its entirety. Technical Field

[0003] The subject matter of this application generally relates to methods and systems for detecting and notifying power outages and power quality in electrical systems. Background Technology

[0004] Consumers continue to rely more heavily on the availability of uninterrupted power for a wide range of activities, such as powering communication equipment, computing devices, medical equipment, heating and cooling appliances, and refrigeration. However, according to the U.S. Energy Information Administration (EIA), in 2016, the average outage time for a U.S. electricity customer was 250 minutes, with an average of 1.3 outages. In 2017, the average outage time nearly doubled, reaching 470 minutes (7.8 hours) on average, with an average of 1.4 outages. The longest outage in 2016 was in the 20-hour range, while in 2017 that figure increased to slightly over 40 hours. Often, these outages are unplanned and, in some cases, may go unnoticed by homeowners, such as those away from home. These outages can have a significant impact on almost every aspect of daily life, including health and safety, making immediate detection and notification of outages crucial.

[0005] Current technologies for detecting power outages typically rely on backup batteries and / or generators, which can temporarily power outage detection equipment and support communication devices. However, batteries have limited lifespan and increase the cost of outage detection equipment. Replacing batteries imposes a continuous maintenance burden on users. Furthermore, in some cases, activation of backup batteries can cause an undesirable delay between the onset of a power outage and the activation of the backup power supply to power the detection equipment.

[0006] Furthermore, power generation, transmission, and distribution systems are becoming increasingly complex. The shift to energy sources that produce less carbon dioxide (CO2) means a combination of many different power generation methods, including wind, solar, nuclear, batteries, natural gas, and coal. Homes and businesses will increasingly adopt on-premise power generation methods, and all these systems are superimposed on power grids that are aging to varying degrees and exposed to the environment. Switching between different power generation types can lead to voltage surges and drops, as well as other power quality issues. Aging and environmental exposure cause transformers and electrical interconnects to deteriorate and fail. Surges, drops, and equipment deterioration can cause malfunctions in household electronic devices and appliances, creating highly dangerous situations that can result in electric shock and electrical fires. In residential environments, fires often begin in walls or other concealed cavities, gaining significant heat and progressing before being detected by occupants or smoke detectors, leading to substantial damage. Electrical faults are one of the leading causes of residential fires.

[0007] Current technology fails to provide homeowners with much-needed information about the quality of the electricity they receive from utilities. For example, homeowners may notice flickering lights or frequent malfunctions in sensitive electronic devices without being alerted to serious problems with their home's electrical connections or network. Furthermore, damage and degradation of the U.S. power grid are increasing the risks and liabilities for both grid utility owners and their customers.

[0008] Many electrical system components (e.g., switches, insulators, transformers) provide decades of trouble-free service, but transmission and distribution components will eventually fail. Wildfires and other property and life losses can be triggered by a variety of mechanisms, including: fallen conductors, vegetation contact, conductor slapping, arcing of damaged or degraded equipment, recurring faults, and equipment failures. Therefore, rapid detection and mitigation of these problems are crucial for preventing catastrophic fire events. Summary of the Invention

[0009] Therefore, there is a need for methods and systems for real-time or near-real-time detection of power outages and power quality in electrical systems, and for notifying relevant users of undesirable changes or hazardous conditions in power systems and / or power quality. The techniques described herein advantageously provide outage detection, power quality assessment, and power system hazard identification based on the frequency of alternating current (AC) received by an outage detection device, and also provide immediate notification of outages to remote devices, including, in some embodiments, the use of communication equipment powered by the power system, which experiences a power outage before the communication equipment goes offline due to the outage. Furthermore, in some embodiments, the methods and systems described herein utilize a single monitoring device or several monitoring devices plugged into existing power outlets, rather than the complex, expensive, or hazardous installation of additional outage detection devices and / or monitoring components (such as those connected to circuit breakers or distribution panels). The techniques described herein not only beneficially provide homeowners and business owners with insights into power quality and potential hazards, but also, in cases where multiple households use the methods and systems described herein, provide utilities with insights into any issues and empower them to proactively address problems before hazards become dangerous.

[0010] In one aspect, the invention features a system for detecting and notifying of power outages. The system includes a server computing device and sensor devices coupled to circuitry. The sensor devices periodically transmit keep-alive packets to the server computing device. The sensor devices detect input signals generated by electrical activity on the circuitry. The sensor devices generate an output signal based on the detected input signals. The sensor devices monitor the generated output signal during each of a plurality of clock cycles having a predefined duration. During each clock cycle, the sensor devices determine whether a rising edge has occurred in the generated output signal and transmit a fault packet to the server computing device before the rising edge occurs at a predetermined clock value in the clock cycle or when no rising edge occurs in the clock cycle. The sensor devices initiate a new clock cycle. The server computing device receives the fault packet from the sensor devices. The server computing device listens for one or more keep-alive packets from the sensor devices. When no keep-alive packet is received from the sensor devices within at least a defined time period after the fault packet is received, the server computing device transmits a power outage notification to one or more remote computing devices. When one or more keep-alive packets are subsequently received from the sensor devices after the power outage notification has been transmitted, the server computing device transmits a power restoration notification to one or more remote computing devices.

[0011] In another aspect, the invention features a computerized method for detecting and notifying of power outages. A sensor device coupled to a circuit periodically transmits keep-alive packets to a server computing device. The sensor device detects an input signal generated by electrical activity on the circuit. The sensor device generates an output signal based on the detected input signal. The sensor device monitors the generated output signal during each of a plurality of clock cycles having a predefined duration. During each clock cycle, the sensor device determines whether a rising edge has occurred in the generated output signal and transmits a fault packet to the server computing device before the rising edge occurs at a predetermined clock value in the clock cycle or when no rising edge occurs in the clock cycle. The sensor device initiates a new clock cycle. The server computing device receives the fault packet from the sensor device. The server computing device listens for one or more keep-alive packets from the sensor device. When no keep-alive packet is received from the sensor device within at least a defined time period after the fault packet is received, the server computing device transmits a power outage notification to one or more remote computing devices. When one or more keep-alive packets are subsequently received from the sensor device after the power outage notification has been transmitted, the server computing device transmits a power restoration notification to one or more remote computing devices.

[0012] Any of the above aspects may include one or more of the following features. In some embodiments, the input signal includes an alternating current (AC) voltage sine wave having multiple zero-crossing points. In some embodiments, the output signal is a voltage profile having multiple rising edges corresponding to the zero-crossing points of the input signal. In some embodiments, the keep-alive group includes power quality data, which includes one or more of the following: root mean square (RMS) voltage, the frequency of the voltage sine wave, the relative phase angle of the voltage sine wave, the amplitude of the voltage sine wave harmonics, or any number of measurements of the amplitude of high-frequency noise. In some embodiments, each clock cycle has a predefined duration of 9 milliseconds. In some embodiments, a predetermined clock value in the clock cycle is 8.33 milliseconds.

[0013] In another aspect, the invention features a system for detecting and notifying power quality. The system includes a server computing device and one or more sensor devices coupled to a circuit. The one or more sensor devices detect an input signal generated by electrical activity on the circuit. The one or more sensor devices generate an output signal based on the detected input signal. The one or more sensor devices transmit power quality data to the server computing device, the power quality data being based on the output signal. The server computing device receives the power quality data from the one or more sensor devices. The server computing device analyzes the power quality data by combining it with historical power quality data received from the one or more sensor devices to detect one or more power quality events. Based on the detected power quality events, the server computing device transmits a power quality notification to one or more remote computing devices.

[0014] In another aspect, the invention features a computerized method for detecting and notifying power quality. A sensor device coupled to a circuit detects an input signal generated by electrical activity on the circuit. The sensor device generates an output signal based on the detected input signal. The sensor device transmits power quality data, based on the output signal, to a server computing device. The server computing device receives the power quality data from the sensor device. The server computing device analyzes the power quality data in conjunction with historical power quality data received from the sensor device to detect one or more power quality events. Based on the detected power quality events, the server computing device transmits power quality notifications to one or more remote computing devices.

[0015] Any of the above aspects may include one or more of the following features. In some embodiments, the detected one or more power quality events include one or more of the following: surge events, surge jump events, droop events, droop jump events, power outage events, surge jump events, high frequency (HF) filter jump events, frequency jump events, recurring power quality problems, phase angle jump events, neutral line loosening events, or generator activation events. In some embodiments, the server computing device further (i) associates the detected one or more power quality events with zero or more external events and / or (ii) associates the power quality events detected from the first sensor device with the power quality events detected from one or more other sensor devices.

[0016] In some embodiments, the server computing device detects a neutral line loosening event by: analyzing, for a single sensor device, the number and magnitude of surge events, surge jump events, and sag events recorded by the single sensor device within a predetermined time period, wherein the surge events, surge jump events, and sag events are not correlated with matching power quality events from any other sensor device near the single sensor device; and generating a neutral line loosening event when the average number of surge events is greater than a first defined number per day, or the average number of surge jump events with a magnitude greater than a defined percentage of the nominal voltage is greater than a second defined number per day, or the average number of sag events is greater than a third defined number per day.

[0017] In some embodiments, the output signal includes one or more of the following: root mean square (RMS) voltage, the frequency of a voltage sine wave, the relative phase angle of the voltage sine wave, the amplitude of voltage sine wave harmonics, or any number of measurements of high-frequency noise amplitude. In some embodiments, the server computing device detects surge events by analyzing multiple sequential data points of RMS voltage from one or more sensor devices; and generating a surge event when the RMS voltage exceeds a predefined threshold percentage of the nominal voltage across multiple consecutive data points. In some embodiments, the predefined threshold percentage varies based on multiple consecutive data points where the RMS voltage exceeds a minimum threshold percentage.

[0018] In some embodiments, the server computing device detects a power-limiting event by analyzing multiple sequential data points of RMS voltage from one or more sensor devices; and generating a power-limiting event when the RMS voltage is less than a predefined threshold percentage of the nominal voltage across multiple consecutive data points. In some embodiments, the predefined threshold percentage varies based on multiple consecutive data points where the RMS voltage is less than a minimum threshold percentage.

[0019] In some embodiments, the server computing device detects droop jump events by analyzing multiple sequential data points of RMS voltage from one or more sensor devices; and generating a droop jump event for each of one or more drops of RMS voltage that occur in the multiple sequential data points and are greater than a predefined threshold percentage of the nominal voltage.

[0020] In some embodiments, the server computing device detects a surge jump event by analyzing multiple sequential data points of RMS voltage from one or more sensor devices; and generating a surge jump event for each of one or more increases of RMS voltage that occur in the multiple sequential data points and are greater than a predefined threshold percentage of the nominal voltage.

[0021] In some embodiments, the server computing device detects HF filter jump events by: analyzing multiple sequential data points of HF amplitude data from one or more sensor devices; calculating the average value of the HF amplitude data; and generating an HF filter jump event when the average value is greater than one, or when the HF amplitude data increases by more than a threshold multiple of the average value, or when the average value is less than one, or when the HF amplitude increases above a predefined threshold.

[0022] In some embodiments, the server computing device detects frequency jump events by: analyzing multiple sequential data points of frequency data from one or more sensor devices; calculating the average value of the frequency data; calculating the standard deviation of the frequency data; and generating a frequency jump event when the frequency increases from the average value by more than a predetermined threshold, or 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 a second frequency to less than a first frequency.

[0023] In some embodiments, the server computing device detects generator activation events by: analyzing whether any power outage events and frequency events are detected by the single sensor device within a predetermined time period for a single sensor device; and generating a generator activation event when the single sensor device detects a power outage event, and the frequency standard deviation changes to a value greater than a predefined threshold within the defined time period of the power outage event, and the change in frequency standard deviation is not associated with any relevant external events.

[0024] In some embodiments, one or more external events include lightning activity events, grid monitoring events, and energy pricing events. In some embodiments, power quality events detected from a first sensor device and power quality events detected from one or more other sensor devices are of the same event type. Such power quality events having the same event type (including but not limited to the same or similar power quality characteristics, duration, start time, stop time, geographical location, etc.) are referred to herein as “related events” or “matching events”.

[0025] Other aspects and advantages of the invention will become apparent from the following detailed description, taken in conjunction with the accompanying drawings which illustrate the principles of the invention by way of example only. Attached Figure Description

[0026] The advantages and further advantages of the invention described above can be better understood by referring to the following description taken in conjunction with the accompanying drawings. The drawings are not necessarily to scale; rather, the emphasis is generally placed on illustrating the principles of the invention.

[0027] Figure 1 This is a block diagram of a system used to detect and notify of power outages.

[0028] Figure 2A and Figure 2B A flowchart of a computerized method for detecting and notifying power outages.

[0029] Figure 3 This is a graph of an exemplary 60 Hz voltage signal captured by a power failure detection device.

[0030] Figure 4 This is a diagram of an exemplary input signal received by the power failure detection device and an exemplary output signal generated by the power failure detection device.

[0031] Figure 5A This is a detailed timing diagram showing the output signal generated by the power failure detection device and the corresponding value of the global power failure flag when the power failure detection device detects a power failure.

[0032] Figure 5B It is a graph of the output signals from multiple different power failure detection devices when a power failure has occurred.

[0033] Figure 6A This is an exemplary user interface of a remote computing device that depicts a power outage notification received from a server computing device.

[0034] Figure 6B This is an exemplary user interface of a remote computing device that depicts a power restoration notification received from a server computing device.

[0035] Figure 7 This is a graph showing the results of testing the detection efficiency of the power failure detection equipment.

[0036] Figure 8 This is a graph of the ITI (CBEMA) curve.

[0037] Figure 9 This is a block diagram of a network system used for power quality detection and notification.

[0038] Figure 10 This is a flowchart of a computerized method for analyzing power quality data.

[0039] Figure 11 This is a graph showing the output signals generated by multiple different power outage detection devices during a power grid surge event.

[0040] Figure 12 It is a graph showing the output signals generated by multiple different power outage detection devices during a power outage event.

[0041] Figure 13 This is a graph showing the output signals generated by multiple different power failure detection devices during a sudden drop event.

[0042] Figure 14 This is a graph showing the output signals generated by multiple different power failure detection devices during a sudden jump event.

[0043] Figure 15 This is a graph showing the output signals generated by multiple different power failure detection devices during an HF filter skipping event.

[0044] Figure 16 It is a graph showing the output signals generated by multiple different power failure detection devices during a frequency jump event.

[0045] Figure 17A It is a graph of the nominal voltage root mean square (RMS) reading captured by the power failure detection equipment.

[0046] Figure 17B This is a graph of the voltage RMS readings captured by a power failure detection device, showing an example of a loose neutral connection.

[0047] Figure 17C This is a graph of the voltage RMS readings captured by the power failure detection equipment before and after resolving a loose neutral wire connection.

[0048] Figure 18 This is a diagram displayed on the user interface of a remote computing device, showing historical voltage RMS readings detected by a power failure detection device.

[0049] Figure 19 This is a diagram of the user interface displayed on a remote computing device, showing a month's worth of power quality events detected by a power outage detection device.

[0050] Figure 20A This is a diagram showing the user interface of a push notification alert sent from a server computing device to a remote computing device for display.

[0051] Figure 20B This is a diagram showing the user interface for a list of power quality notifications related to the power outage detection equipment.

[0052] Figure 20C This is a diagram showing the user interface of a detailed power surge event alarm notification sent from a server computing device to a remote computing device for display.

[0053] Figure 20D This is a diagram showing the user interface of a detailed power outage event alarm notification sent from a server computing device to a remote computing device for display.

[0054] Figure 20E This is a diagram showing the user interface of a recurring power quality problem alarm notification sent from a server computing device to a remote computing device for display. Detailed Implementation

[0055] Figure 1 This is a block diagram of a system 100 for detecting and notifying of power outages. System 100 includes a power outage detection device 102, a communication medium 104, and a remote computing device 106. The power outage detection device 102 includes an optical isolator 102a connected to the hot and neutral lines of the power system to monitor current (e.g., 120 VAC, 60 Hz) for the purposes described herein. The optical isolator 102a is also connected to ground (GND). Figure 3 An exemplary 60 Hz voltage signal captured by a power outage detection device is shown. Optical isolator 102a generates an output signal (Out) based on the received current, which is provided to a processor 102b of the power outage detection device 102. Processor 102b analyzes the output signal from optical isolator 102a and transmits data (e.g., packet-based communication) to server computing device 106, which can then transmit a power outage notification to one or more remote computing devices (not shown) based on the data received from the power outage detection device 102. The exemplary power outage detection device 102 is a Ting™ sensor available from Whisker Labs, Germanytown, Maryland.

[0056] The power outage detection device 102 also includes an analog-to-digital (A / D) converter 102c, which reads input signals from the hot and neutral lines. In some embodiments, the input signals may be filtered or transformed before being read by the A / D converter 102c. The A / D converter 102c generates certain power quality data to be sent to a server, including but not limited to RMS voltage, peak voltage, frequency, phase, high-frequency (HF) amplitude, and harmonic amplitude. It is understood that other power quality measurements may be calculated, and this list is not intended to be exhaustive. Power quality data is periodically transmitted to the server computing device at regular time intervals and is included as... Figure 1 This is a portion of the "keep-alive packet" shown and described in this article.

[0057] Communication medium 104 enables other components of system 100 to communicate with each other in order to perform the process of detecting and notifying power outages as described herein. Medium 104 may be a local area network, such as a LAN including one or more components (e.g., a router, modem) connected to a power line monitored by system 100, or a wide area network, such as the Internet and / or a cellular network. In some embodiments, network 104 comprises several discrete networks and / or subnetworks (e.g., cellular-to-Internet) that enable components of system 100 to communicate with each other. Communication medium 104 may include wired and / or wireless components.

[0058] Server computing device 106 is a combination of hardware (including one or more dedicated processors and one or more physical memory modules) and dedicated software modules executed by the processor of server computing device 106 to receive data from other components of system 100, transfer data to other components of system 100, and perform functions for detecting and notifying of power outages, as described herein. In some embodiments, server computing device 106 includes an alarm module 106, which is a set of dedicated computer software instructions programmed into a dedicated processor in server computing device 106, and may include specially designated memory locations and / or registers for executing the dedicated computer software instructions. Further explanation of specific processes performed by alarm module 106a will be provided below.

[0059] As can be understood, in certain circumstances, it is beneficial to correlate other external events (e.g., events outside the power grid / power system) with power quality events. For example, if a lightning strike is closely associated with a surge power quality event, System 100 can issue more urgent notification warnings to end users (e.g., visual and audible alarm messages on multiple end-user devices), especially if the surge event is of a magnitude that could cause significant damage to appliances in the home. If a homeowner knows that a direct lightning strike caused a very strong surge, he or she may be extra vigilant to monitor for direct hazards in their home. Correlating power quality events with other grid monitoring devices (such as automatic recloser devices) can also be beneficial. In this way, utilities can use the techniques described herein to correlate events from recloser devices with power quality events in homes or businesses. External events can be correlated with power quality events to limit power distribution or increase the urgency of notifications to end users.

[0060] In some embodiments, the power failure detection device 102 is coupled via a 120 VAC plug to a socket in a branch circuit of the building's electrical system, which in turn is connected to the public power grid. Although Figure 1A single power outage detection device 102 is depicted; however, it should be understood that system 100 may include two or more power outage detection devices positioned to sense electrical activity in the power distribution system. Multiple sensors sending data to a server computing device can provide increased sensitivity and work together to provide information about power outages and power quality in the power system and / or grid. It should be further understood that multiple power outage detection devices may be installed in a single location (e.g., a home), and system 100 may also be configured to receive data from multiple power outage detection devices, each installed in a different location (see reference below). Figure 9 (as described).

[0061] As described above, the power failure detection device 102 is communicatively coupled to the server computing device 106 via the communication medium 104. In one embodiment, the power failure detection device 102 is equipped with communication components (e.g., antenna, network interface circuitry) that enable the power failure detection device 102 to communicate with the server computing device 106 via a wireless connection (i.e., using wireless components, such as a router and / or modem, communication medium 104).

[0062] Figure 2A and Figure 2B Including the use Figure 1 A flowchart of a computerized method 200 for detecting and notifying power outages in system 100. A power outage detection device (e.g., power outage detection device 102) coupled to a branch circuit of the power distribution system detects (202) an input signal generated by electrical activity on the branch circuit. Power outage detection device 102 generates (204) an output signal based on the detected input signal. Figure 4 This is a diagram of an exemplary input signal 402 received by the power failure detection device 102 and an exemplary output signal 404 generated by the power failure detection device 102. Figure 4 As shown, the input signal 402 includes a typical alternating current (AC) voltage signal (such as an AC sine wave), whose zero-crossing points (e.g., 402a, 402b) occur approximately 8.33 milliseconds (ms) apart.

[0063] The optical isolator 102a of the power failure detection device 102 receives the input signal 402 via a hot-wire connection and a neutral-wire connection to the power distribution system (including the power grid), and converts the input signal 402 into an output signal 404. For example... Figure 4 As shown, the output signal 404 includes a voltage curve with multiple rising edges (e.g., 404a, 404b), which typically correspond to the zero-crossing points of the input signal 402, since the rising edges occur at intervals of approximately 8.33 ms. Figure 4Figure 406 illustrates the superimposed input signal 402 and output signal 404 to show the correspondence between the signals. It should be understood that, depending on the electrical system to which the power failure detection device 102 is coupled (including the spectrum of electronic devices that can be coupled to the electrical system), one or more distinct points on multiple rising edges of the output signal 404 may correspond to zero-crossing points of the input signal 402 (e.g., the start point of a rising edge in the output signal 404 may correspond to a zero-crossing point of the input signal 402, the midpoint between the start point and the peak of the rising edge may correspond to a zero-crossing point, or the peak of the rising edge may correspond to a zero-crossing point). It should be further understood that the identical points (e.g., start point, midpoint, peak) on each rising edge should occur approximately 8.33 m apart. The output signal 404 is transmitted to a processor embedded in the power failure detection device (see...). Figure 1 The processor monitors output signal 404, as described below. It should be understood that the exact timing of the zero-crossing point described herein is for illustrative purposes only and corresponds to the standard timing of the US power system. The algorithms and techniques described herein can be modified to automatically detect and adjust to different timings for the international power system.

[0064] Return to Figure 2A When the power failure detection device 102 is powered on and connected to the server computing device 106, the power failure detection device 102 periodically sends (206) keep-alive packets to the alarm module 106a of the server computing device 106. The keep-alive packets are used to notify the server computing device 106 that the power failure detection device 102 is receiving power (i.e., there is no power failure at the corresponding location) and that the power failure detection device 102 is online. For example, the processor 102b of the power failure detection device 102 executes a continuously running main thread and sends keep-alive packets to the server computing device 106 at regular ¼-second intervals. In some embodiments, the keep-alive packets may additionally include other periodically monitored data generated by the A / D converter 102c as described above, such as any number of measurements of the root mean square (RMS) voltage of the power distribution system, the frequency of the voltage sine wave, the relative phase angle of the sine wave, the amplitude of the sine wave harmonics, and the amplitude of high-frequency noise. Examples of certain non-limiting types of power quality data that can be captured and transmitted by a power failure detection device 102 are described in U.S. Patent No. 10,641,806 entitled “Detection of Electric Discharges that PrecedeFires in Electrical Wiring”, which is incorporated herein by reference.

[0065] In addition, the main thread monitors a global power-off flag. When the power-off flag is set (e.g., set to 1), the main thread sends a fault packet (e.g., indicating a power outage) to the server computing device 106 and resets the power-off flag to 0. Additional details regarding the power-off flag and fault packets are described below.

[0066] The power failure detection device 102 monitors (208) the generated output signal during each of a plurality of clock cycles having a defined duration. For example, the processor 102b of the power failure detection device 102 can create a timer (or timeout clock) that counts down from 9 ms (approximately 55 Hz frequency) to zero and then resets. When the timer reaches zero, the processor 102b invokes an interrupt to the main thread (“timeout interrupt”). Furthermore, when the processor detects an output signal received from the opto-isolator 102a (i.e., Figure 4 When the rising edge of signal 404 occurs, processor 102b invokes an interrupt to the main thread (“optical isolator interrupt”).

[0067] When processor 102b invokes the opto-isolator interrupt, processor 102b of power-off detection device 102 determines (210) whether a rising edge occurs in the generated output signal 404. For example, processor 102b counts how many clock ticks have occurred since the last opto-isolator interrupt time. This indicates a power loss when (i) a rising edge occurs in the generated output signal 404 before a predetermined clock value in the clock cycle (e.g., if the last optical isolator interrupt occurred less than 7.6 ms ago (approximately 65 Hz frequency), or (ii) no rising edge occurs in the generated output signal 404 during the clock cycle (e.g., the last optical isolator interrupt occurred more than 9 ms ago, thus triggering the aforementioned timeout interrupt). As a result, processor 102b sets the global power-down flag to 1. As described above, the main thread executed by processor 102b is monitoring the global power-down flag, and when the main thread sees the flag set to 1, the processor of output detection device 102 sends (212) a fault group to alarm module 106a of server computing device 106 and initiates (214) a new clock cycle for monitoring the generated output signal 404 (e.g., by reloading or resetting the timeout clock to 9 ms).

[0068] Figure 5A This is a detailed timing diagram showing the output signal generated by the power failure detection device 102 and the corresponding value of the global power failure flag when the power failure detection device 102 detects a power failure. For example... Figure 5AAs shown, trace 510 corresponds to the output signal 404 generated by the power failure detection device 102. The solid black line 502 indicates the value of the global power failure flag in the main thread of processor 102b, while the dashed black line 504 indicates when the main thread completes sending a fault packet to server computing device 106. For example, processor 102b detects a power failure at time t1 and sets the global power failure flag to 1. Then, at time t2, the main thread of processor 102b reads the global power failure flag as 1 and begins sending a fault packet to server computing device 106. At time t3, the main thread completes sending the fault packet to server computing device 106. Processor 102b detects a second power failure at time t4 (which may correspond to the same overall power failure) and begins transmitting a second fault packet to server computing device at time t5. Then, at time t6, processor 102b completes sending the second fault packet.

[0069] Alternatively, when the rising edge occurs in the output signal 404 at a predetermined clock value in the clock cycle (i.e., approximately 8.33 ms), the opto-isolator interrupt procedure does not set the global power-down flag to 1 (and the timeout interrupt is not triggered). As a result, the processor 102b of the output detection device 102 simply initiates (214) a new clock cycle to monitor the generated output signal 404 (e.g., by reloading or resetting the timeout clock to 9 ms).

[0070] Figure 5B This is a graph showing the output signals from multiple different power outage detection devices when a power outage has occurred. For example... Figure 5B As shown, each line (e.g., line 512) corresponds to a voltage reading from the output signal of a different power outage detection device. Shortly before 05:48, a power outage occurred, reflected at line t1 in the diagram, where the readings from each device abruptly ceased. Over the next few minutes, power was restored to each of the power outage detection devices at different times, indicated by arrows labeled "Power Restoration".

[0071] Go to Figure 2B In the event that the power failure detection device 102 transmits a fault packet to the server computing device 106, the alarm module 106a receives (216) the fault packet from the power failure detection device 102 and listens (218) for keep-alive packets from the power failure detection device 102. As previously described, the main thread of the processor 102b of the power failure detection device 102 is configured to transmit a keep-alive packet to the server computing device every ¼ second. When the alarm module 106a receives the fault packet, and no keep-alive packet is subsequently detected within at least a defined time period (e.g., 5 seconds) after the fault packet is received, the alarm module 106a transmits (220) a power failure notification to one or more remote computing devices.

[0072] In some embodiments, the alarm module 106a may transmit power outage notifications to remote computing devices (e.g., mobile phones, smartwatches, smart devices, tablets, laptops, etc.) via one or more communication channels and / or communication protocols (such as email, text (e.g., SMS), automated phone calls). In some embodiments, the alarm module 106a may transmit power outage notifications to computing devices associated with different organizations via, for example, webhook API callbacks or by utilizing services from cloud computing providers (such as Amazon Web Services (AWS) Simple Notification Service). In one example, the remote computing device may include a mobile application configured to: receive push notifications from the alarm module 106a; and, upon receiving a push notification, automatically activate functionality of the mobile application to alert the user of the remote computing device (e.g., pop-up messages, audible alarms, and / or haptic alarms (vibration)) that a power outage is occurring at the corresponding location of the power outage detection device 102. Figure 6A This is an exemplary user interface depicting a remote computing device (e.g., a smartphone) receiving a power outage notification from alarm module 106a. Figure 6A As shown, the power outage notification includes a visual symbol 602 indicating a power outage event and a detailed description 604 including the time and location of the power outage.

[0073] After transmitting the power outage notification, the alarm module 106a returns to listening for keep-alive packets from the power outage detection device 102. When the alarm module 106a subsequently detects one or more keep-alive packets (within a defined time period or after the defined time period has elapsed) after the power outage notification has been transmitted, the alarm module 106a transmits (222) a power restoration notification to one or more computing devices. As described above regarding the power outage notification, a remote computing device can receive the power restoration notification from the alarm module 106a and activate the remote computing device's functionality to alert the device's user that power has been restored. Figure 6B This is an exemplary user interface of a remote computing device depicting a power restoration notification received from alarm module 106a. (Example:) Figure 6B As shown, the power restoration notification includes a visual symbol 606 indicating a power restoration event and a detailed description 608 including the time and location of the power restoration.

[0074] It should be understood that the reliability of the power outage detection method described herein may depend on the connectivity between the power outage detection device 102 and the server computing device 106, and on the availability of intermediate equipment supporting that connectivity. For example, the power outage detection device 102 may be connected to a local WiFi router (e.g., installed in a home or business), which in turn is connected to an internet modem or router, which in turn is connected to other components within the network of the corresponding internet provider before the connection finally reaches the server computing device 106 that detects the power outage event. As a result, before one or more of these devices lose power and are unable to transmit, retransmit, and / or relay fault packets to the next link in the entire connection, fault packets must be sent by the power outage detection device 102, traversing each segment of the communication medium 104 (e.g., a network), which may or may not be powered by the same power distribution system and power lines. It should be understood that if fault packets do not reach the server computing device 106, the server computing device 106 cannot distinguish whether keep-alive packets are stopped due to a loss of communication connectivity (e.g., internet interruption) or due to a power outage at the location of the power outage detection device 102. Therefore, rapid detection of power outages and transmission failure packets is crucial to the advantages offered by the methods and systems described in this paper.

[0075] To determine the effectiveness of this method for detecting power outages, tests were conducted using two power outage detection devices placed in two different locations. Each device was placed on a programmable switch so that the power could be automatically switched off once a day for several months. Figure 7 It is a graph showing the test results. For example... Figure 7 As shown, the power failure detection device 102 successfully detected the power failure on average 95% of the time, with a maximum detection efficiency of 100% and a minimum detection efficiency of 71%.

[0076] Furthermore, it should be understood that another advantage provided by the technology described herein is that the efficiency of power outage detection and notification is improved as the installation ranges of the power outage detection devices are close to each other. For example, the efficiency of detecting power outages is improved when multiple power outage detection devices are close to each other (e.g., on the same voltage transformer supplying power to multiple homes). If the power outage detection device 102 installed in at least one home on the same electrical network is able to transmit fault packets to the server computing device 106, and simultaneously keep-alive packets stop arriving, then a power outage notification can be sent to the remote device associated with each customer on the network. The same method can be used for power grid outages over a wider area: if dozens of homes are supplied by the same substation, then in the event of a power outage at that substation, only one power outage detection device 102 installed at a single home among the dozens of homes served by the substation needs to successfully transmit fault packets to the server computing device 106 in order to generate a power outage notification to the remote device associated with the customer in each of the dozens of homes. Conversely, if dozens of homes are powered by the same substation, and the outage detection device 102 installed at each home does not transmit fault packets before the communication of keep-alive packets is lost, then it is safe to assume that the outage is the result of another non-power-related event (e.g., an Internet service provider (ISP) outage) rather than the result of a loss of power.

[0077] Another key feature of the method and system described herein is the ability to monitor the power quality of the power received by the power outage detection device 102 of system 100 and provide power monitoring-related information to both customers (e.g., homeowners who installed the power outage detection device 102) and utility providers. As previously mentioned, the power outage detection device 102 can capture additional data about the power during its periodic monitoring of power outages (such as, for example, any number of measurements of the root mean square (RMS) voltage of the distribution system, the frequency of the voltage sine wave, the relative phase angle of the sine wave, the amplitude of the sine wave harmonics, and the amplitude of high-frequency noise), and the power outage detection device 102 can transmit the data to the server computing device 106 (e.g., as part of transmitting keep-alive packets to the server computing device).

[0078] As will be described in more detail below, the power failure detection device 102 can send a 5 Vrms voltage sample to the server computing device 106 every ¼ second (or 20 Vrms readings per second). This enables the server computing device 106 to monitor voltage surges and drops that could potentially damage electrical or sensitive electronic equipment also coupled to the power distribution system. Figure 8This is a graph called the ITI (CBEMA) curve. This graph shows the acceptable voltage level within the voltage amplitude envelope over a period of time. For example, a very short duration (approximately 16 milliseconds) of a large voltage amplitude (300 volts) typically will not affect equipment powered on the circuit, but if the voltage amplitude remains at 300 volts for more than 5 seconds, it can damage any equipment on the electrical network. Furthermore, when a single location experiences multiple power outages, surges, or drops over several days, customers are advised to contact their power company. Recurring power quality problems can damage appliances and sensitive electronic equipment and may indicate a more serious problem with the power lines entering the residence, potentially leading to an electrical fire.

[0079] For example, if the amplitude and duration of the voltage data flowing to alarm module 106a exceed the boundary of the CBEMA curve above the nominal voltage level, alarm module 106a sends a "power surge" notification message to the end user's equipment. If the amplitude and duration of the voltage data flowing to alarm module 106a exceed the boundary of the CBEMA curve below the nominal voltage level, alarm module 106a sends a "power restriction" notification to the end user's equipment.

[0080] In some embodiments, other information collected from the voltage signal can also indicate power quality problems. For example, a measurement of the frequency of a voltage sinusoidal wave with a very high variance might indicate that the household is no longer using utility power and has switched to a standby generator. A large jump in the sinusoidal wave frequency might indicate that something has changed in the power grid, such as a power plant going offline. This typically causes a significant drop in frequency. Alternatively, the event might indicate that a new power plant has come online, which can cause a significant jump in frequency. System 100 can use algorithms to detect that a generator in the home has been turned on, such as measuring the frequency variance over the previous five seconds, and if the variance exceeds a threshold, System 100 can send a notification to the end-user's device and / or utility monitoring device that the household is now using generator power after a power outage has been detected. When the frequency variance falls back to normal variance, System 100 can send a notification that the household has been restored to utility power.

[0081] While larger deviations in RMS voltage outside the limits of the CBEMA curve cause the most damage to home appliances, smaller changes in RMS voltage can serve as an indicator of home activity, potentially warning the homeowner of equipment malfunctions or hazards. One such hazard is called a loose neutral. A loose neutral occurs when the neutral wire, which normally holds the voltage level in a home to "ground," breaks. The result of a loose neutral is significantly more unstable voltage across individual legs and includes a much higher rate of jumps in the positive direction (voltage increase). This is due to the impedance imbalance on each leg as individual appliances on and off. Large appliances operating at 220V will not produce any noticeable difference in voltage jumps.

[0082] In addition, when a single location experiences multiple power outages, surges, or sudden drops over several days, customers are advised to contact their power company. Recurring power quality problems can damage appliances and sensitive electronic equipment and may indicate a more serious problem with the power lines entering the residence, potentially leading to an electrical fire. Recurring power quality problems may be limited to a single household, in which case it might be due to a loose neutral wire, or they may occur regularly in households connected to the same transformer or substation. In these cases, recurring power quality problems may indicate a fault at the common transformer or substation.

[0083] Figure 9 This is a block diagram of the Power Quality Detection and Notification Network System 900. Figure 9 System 900 uses many of the features mentioned above. Figure 1 The same device is being described, so those descriptions will not be repeated here. Figure 9As shown, system 900 includes multiple power outage detection devices 902, 910, 912 installed at different locations (e.g., homes, businesses) within a geographic area. These power outage detection devices 902, 910, 912 provide power quality data as described above to server computing device 906 via communication network 904. Server computing device 906 uses one or more power quality analysis algorithms (as will be described below) to analyze the power quality data received from the multiple power outage detection devices 902, 910, 912 to detect power quality events and generate event notification messages that are distributed to one or more remote computing devices 908a, 908b controlled by end users (e.g., homeowners, business owners, utilities, etc.). It should be understood that the power outage detection device (e.g., device 902) may be located in the same location as a remote computing device (e.g., device 908a). For example, a homeowner may install the power outage detection device 902 in his or her home and view the notification message at any of several different computing devices associated with the homeowner (such as computing devices located in the home or mobile devices carried by the user).

[0084] Figure 10 Is using Figure 9 The flowchart illustrates a computerized method for analyzing power quality data using system 900. Upon receiving power quality data, server computing device 906 detects (1002) one or more power quality events based on the received power quality data. Server computing device 906 can store the captured power quality data as historical data for future reference, as described herein. In some instances, it may be understood that no power quality event occurred in the power quality data received by server computing device 906, and therefore no further action is taken.

[0085] When one or more power quality events are detected, server computing device 906 associates the detected power quality events with one or more external events that may have contributed to or affected the power quality events (1004). For example, lightning strikes or other weather activities may have occurred in the same geographic area as the homes or businesses monitored by outage detection devices 902, 910, 912. In another example, grid equipment may have executed an automatic reclosing event, where a circuit recloser on the grid senses a fault condition and temporarily cuts off power to a portion of the grid serving the homes and businesses equipped with outage detection devices 902, 910, 912. In yet another example, changes in power demand on certain parts of the grid (e.g., energy pricing events) may occur, affecting the power quality of homes or businesses utilizing outage detection devices 902, 910, 912.

[0086] Once the association steps are complete, server computing device 906 uses one or more power quality algorithms as described herein to analyze (1006) power quality events and external events. It should be understood that the power quality algorithms are exemplary, and other types of algorithms may be used with the methods and systems described herein. Furthermore, it should be understood that in some embodiments, power outage detection devices 902, 910, 912 installed at each location may perform some or all of the power quality analyses described herein that are performed by server computing device 906 (e.g., for providing real-time customized power quality analysis for a specific location).

[0087] After analyzing power quality events and external events, server computing device 906 performs (1008) historical power event analysis for, for example, a specific location, geographical area, and / or any number of power outage detection devices 902, 910, 912. As described above, the system can utilize historical event data to detect recurring power quality problems (e.g., sags, surges, etc.) that may indicate structural defects in the power grid and / or home wiring system (e.g., a loose neutral wire), and these power quality problems can only be detected by analyzing power quality data over a longer period of time (e.g., days, weeks, or months). Finally, server computing device 906 transmits (1010) one or more event notification messages (e.g., alarm messages) based on the aforementioned power event analysis. These one or more event notification messages are then distributed to one or more remote computing devices 908a, 908b, as will be described in more detail below.

[0088] The general structure of a power quality algorithm executed by a server computing device is as follows:

[0089] 1. The server computing device 906 captures and arranges several seconds of incoming power quality data.

[0090] 2. The server computing device 906 detects power quality events in incoming power quality data based on predefined data types and predefined rules (e.g., determined according to a historical data queue), including performing one or more specific power quality algorithms on the incoming data. The server computing device 906 marks detected power quality events with certain data points, such as: the time of the event, the location of the event, and various detection or calculation quantities associated with the event (e.g., any number of measurements of the root mean square (RMS) voltage of the distribution system, the frequency of the voltage sine wave, the relative phase angle of the sine wave, the amplitude of the sine wave harmonics, and the amplitude of high-frequency noise).

[0091] 3. Server computing device 906 adds detected power quality events to an event association queue to detect associated events (i.e., events from multiple power outage detection devices or external events). For example, external event data may be obtained from one or more remote computing devices. In the event of a lightning strike, server computing device 906 may, for example, communicate with a server in a lightning detection network to identify the lightning event. As can be understood, associated events typically occur within the time difference (delta) of the aforementioned detected power quality events, within the location difference of the power outage detection devices 902, 910, and 912, and are typically of the same type (including but not limited to the same or similar power quality characteristics, duration, start time, stop time, geographical location, etc.). In some embodiments, a minimum number of power outage detection devices may be required before detecting associated events to minimize false detections.

[0092] 4. The server computing device 906 stores the detected power quality events and related events to, for example, long-term storage, such as a NoSQL database or other types of archive storage.

[0093] 5. The server computing device transmits power quality notification messages to one or more remote computing devices 908a, 908b based on detected power quality events, related events, and historical events in some embodiments (e.g., generated by tracking power quality data of specific power outage detection devices 902, 910, 912 and / or geographical areas over a period of time).

[0094] The following are examples of algorithms that can be used by the server computing device 906 to detect specific power quality conditions and events.

[0095] Surge events

[0096] Surge events typically occur when conditions on the power grid cause excessive voltage to be delivered to households. To detect surge events, the server computing device 906 can analyze incoming power quality data as follows.

[0097] 1. The server computing device 906 captures and arranges the incoming RMS voltage data for a defined amount (e.g., six seconds).

[0098] 2. If the server computing device 906 determines that the RMS voltage exceeds a predefined threshold percentage (e.g., 120%) of the nominal voltage across multiple consecutive data points (or otherwise falls outside the upper part of the CBEMA curve), the server computing device 906 adds a “surge” event along with information such as: the UTC time of the event, the location associated with the installation point of the power outage detection device capturing the incoming data (e.g., location data, such as GPS, latitude / longitude, cellular-based data, etc.), and the maximum value of the RMS voltage. It should be understood that, in one embodiment, the predefined threshold percentage may vary based on multiple consecutive data points where the RMS voltage is greater than a minimum threshold percentage.

[0099] 3. The server computing device 906 adds the detected surge event to be evaluated, along with other surge events, to a correlated event queue. The correlated event queue is evaluated to generate correlated events. As an example, correlated events include “grid surge events” within a defined time period (e.g., 400 milliseconds) and a defined proximity (e.g., ten kilometers) of the detected surge event. In some embodiments, a minimum number of events may be required to reach an agreement.

[0100] 4. The server computing device 906 stores the detected surge events and associated power grid surge events in, for example, long-term storage.

[0101] 5. Server computing device 906 transmits alarm notification messages related to the detected surge event and associated events to remote computing devices 908a (such as mobile phones, smart devices, wearable devices, etc.) associated with the individual homeowners to whom the surge event has been detected, and / or transmits notification messages related to the detected surge event and associated events (including external events, if detected) to remote computing devices 908b of relevant utilities or other power grid operators.

[0102] Figure 11 This is a graph showing the output signals generated by multiple different power outage detection devices during a power grid surge event. For example... Figure 11 As shown, each line in the figure (e.g., line 1102) represents the output signal from a different power outage detection device. Around 14:17:10 (time t1), a surge event occurs, resulting in a power outage. The RMS voltage signal received by the server computing device 906 from each power outage detection device increases significantly from their previous levels, indicating that the power outage detection device has received a voltage surge.

[0103] Power rationing

[0104] Typically, a power outage occurs when conditions on the power grid cause a sustained drop in the voltage delivered to households. To detect a power outage, the server computing device 906 can analyze incoming power quality data as follows.

[0105] 1. The server computing device 906 captures and arranges RMS voltage data of a defined quantity (e.g., six seconds).

[0106] 2. If the server computing device 906 determines that the RMS voltage is less than a predefined threshold percentage (e.g., 70%) of the nominal voltage across multiple consecutive data points (or otherwise below the CBEMA curve), the server computing device 906 adds a "power-limited" event along with information such as the event's UTC time, location, and the minimum RMS voltage to the event queue. It should be understood that, in one embodiment, the predefined threshold percentage may vary based on multiple consecutive data points where the RMS voltage is less than the minimum threshold percentage.

[0107] 3. The server computing device 906 adds the detected power curtailment event to be evaluated, along with other power curtailment events, to a correlated event queue. The correlated event queue is evaluated to generate correlated events. As an example, correlated events include “grid curtailment events” within a defined time period (e.g., 400 milliseconds) and a defined proximity (e.g., ten kilometers) of the detected power curtailment event. In some embodiments, a minimum number of events may be required to reach an agreement.

[0108] 4. The server computing device 906 stores the detected power rationing events and associated power grid power rationing events in, for example, long-term storage.

[0109] 5. Server computing device 906 transmits alarm notification messages related to the detected power curtailment event and related events to remote computing device 908a associated with the individual homeowner to whom the power curtailment event has been detected, and / or transmits notification messages related to the detected power curtailment event and related events to remote computing device 908b of the relevant utility or other grid operator.

[0110] Figure 12 This is a graph showing the output signals generated by multiple different power outage detection devices during a power shortage event. For example... Figure 12 As shown, each line in the figure (e.g., line 1202) represents the output signal from a different power failure detection device. Around 21:02:34 (time t1), a power failure event occurs. The voltage RMS signal received by the server computing device 906 from each power failure detection device drops significantly over several cycles before returning to approximately the same voltage level, indicating that a power failure event was detected at the power failure detection device.

[0111] Sudden Jump Event

[0112] A sag event typically occurs when conditions on the power grid cause a brief drop in the voltage delivered to a household. To detect sag events, the server computing device 906 can analyze incoming power quality data as follows.

[0113] 1. The server computing device 906 captures and arranges RMS voltage data of a defined quantity (e.g., six seconds).

[0114] 2. The server computing device 906 determines whether one or more RMS voltage drops have occurred that are greater than a predefined threshold percentage (e.g., 2.5%) of the nominal voltage, and the server computing device 906 generates a “sag jump” event for each detected voltage drop.

[0115] 3. The server computing device 906 adds the detected drop jump events (including, for example, the event's UTC time, location, and maximum RMS voltage drop) to the associated event queue.

[0116] 4. The server computing device 906 evaluates all drop-over events in the associated event queue to identify drop-over events that occur within a defined time period (e.g., 400 milliseconds) and a defined proximity (e.g., ten kilometers) to each other. In some embodiments, a minimum number of events may be required to identify associated events.

[0117] 5. Server computing device 906 stores the identified drop jump events and related events in, for example, long-term storage.

[0118] 5. Server computing device 906 transmits alarm notification messages related to the detected drop jump events and associated events to remote computing device 908a associated with individual homeowners whose drop jump events have been detected, and / or transmits notification messages related to the drop jump events and associated events to remote computing devices 908b of relevant utilities or other power grid operators.

[0119] Figure 13 This is a graph showing the output signals generated by multiple different power failure detection devices during a sudden drop event. For example... Figure 13 As shown, each line in the figure (e.g., line 1302) represents the output signal from a different power failure detection device. Around 21:02:35 (time t1), a sag-jump event occurs. The RMS voltage signal received by the server computing device 906 from each power failure detection device drops significantly and then returns to approximately the same voltage level almost immediately, indicating that a sag-jump event was captured at the power failure detection device.

[0120] Sudden Jump Event

[0121] A scaling event typically occurs when conditions on the power grid cause an increase in the voltage delivered to a household. In some cases, a scaling event may also occur when a heavy load in the electrical system is switched off. To detect scaling events, the server computing device 906 can analyze incoming power quality data as follows.

[0122] 1. The server computing device 906 captures and arranges RMS voltage data of a defined quantity (e.g., six seconds).

[0123] 2. The server computing device 906 determines whether one or more RMS voltage increases have occurred that are greater than a predefined threshold percentage (e.g., 2.5%) of the nominal voltage, and the server computing device 906 generates a “surge jump” event for each detected voltage increase.

[0124] 3. The server computing device 906 adds the detected surge jump events (including, for example, the event's UTC time, location, and the maximum value of the RMS voltage increase) to the associated event queue.

[0125] 4. The server computing device 906 evaluates all spurious jump events in the associated event queue to identify spurious jump events that occur within a defined time period (e.g., 400 milliseconds) and a defined proximity (e.g., ten kilometers) to each other. In some embodiments, a minimum number of events may be required to identify associated events.

[0126] 5. The server computing device 906 stores the identified surge jump events and related events in, for example, long-term storage.

[0127] 6. Server computing device 906 transmits alarm notification messages related to the detected (multiple) surge jump events and associated events to remote computing device 908a associated with individual homeowners whose (multiple) surge jump events have been detected, and / or transmits notification messages related to the (multiple) surge jump events and associated events to remote computing devices 908b of relevant utilities or other grid operators.

[0128] Figure 14 This is a graph showing the output signals generated by multiple different power failure detection devices during a sudden jump event. For example... Figure 14 As shown, each line in the figure (e.g., line 1402) represents the output signal from a different power failure detection device. Around 01:33:50 (time t1), a sag-jump event occurs. The voltage RMS signal received by the server computing device 906 from each power failure detection device increases to a higher voltage level almost immediately, indicating that a sag-jump event has been captured at the power failure detection device.

[0129] High Frequency (HF) Filter Events

[0130] As described above, power outage detection devices 902, 910, and 912 can monitor certain power quality data, including the high-frequency amplitude of incoming power, which may damage wiring and appliances in the home. To detect high-frequency filter events, server computing device 906 can analyze the incoming power quality data as follows.

[0131] 1. Server computing device 906 captures and arranges high-frequency (HF) amplitude data of a defined amount (e.g., six seconds).

[0132] 2. Server computing device 906 calculates the sliding mean of the high-frequency (HF) amplitude data. If the mean is greater than one, server computing device 906 generates an HF filter event when the HF amplitude data jumps by a predefined multiple (e.g., five) of the mean. If the mean is less than one, server computing device 906 generates an event when the HF amplitude data jumps by a predefined threshold (e.g., five). It is understood that in some embodiments, the selected jump threshold used to identify the HF filter event may vary based on different signal-to-noise ratio thresholds or other characteristics of the HF data.

[0133] 3. Server computing device 906 adds (multiple) HF filter events (including, for example, the UTC time, location, and magnitude of the HF amplitude jump of the event) to the associated event queue.

[0134] 4. The server computing device 906 evaluates all HF filter jump events in the associated event queue to identify HF filter events that occur within a defined time period (e.g., 400 milliseconds) and a defined proximity (e.g., ten kilometers) to each other. In some embodiments, a minimum number of events may be required to identify associated events.

[0135] 5. The server computing device 906 stores the identified (multiple) HF filter events and associated events into, for example, long-term storage.

[0136] 6. Server computing device 906 transmits alarm notification messages related to the detected HF filter events and associated events to remote computing device 908a associated with individual homeowners whose HF filter events have been detected, and / or transmits notification messages related to the HF filter events and associated events to remote computing devices 908b of relevant utilities or other grid operators.

[0137] Figure 15 This is a graph showing the output signals generated by multiple different power failure detection devices during an HF filter skipping event. (Example) Figure 15As shown, each line in the figure (e.g., line 1502) represents the output signal from a different power failure detection device. Around 14:15:20 (time t1), an HF filter skipping event occurs. The frequency signals received by the server computing device 906 from each power failure detection device almost immediately increase to higher levels and become much noisier due to the wide frequency variation in each signal, indicating that an HF filter skipping event was captured at the power failure detection device.

[0138] It should be understood that the system can be further configured to detect initial arcing events on the power grid. For example, when the system detects multiple HF filter events over time without any change in the voltage or frequency of the phase angle, the system can determine that the HF filter events correspond to an initial arcing event, thereby detecting a dangerous situation at a very early stage. The system can then alert the grid operator and / or utility provider to the presence of an arcing condition, as well as the possible geographical area or location of the condition, so that the operator can quickly assess and remedy the problem.

[0139] Frequency events

[0140] As described above, power outage detection devices 902, 910, and 912 can monitor certain power quality data, including the frequency of power entering the home. The frequency of this power flow can, under certain circumstances (including sudden increases or decreases), damage the wiring and appliances in the home. To detect frequency events, server computing device 906 can analyze the incoming power quality data as follows.

[0141] 1. The server computing device 906 captures and arranges frequency data of a defined quantity (e.g., six seconds).

[0142] 2. Server computing device 906 calculates the moving average of the frequency data. If the frequency jumps from the average value by more than a predefined threshold (e.g., 0.05 Hz), server computing device 906 generates a frequency event. Server computing device 906 also calculates the standard deviation of the frequency and generates a frequency event if (i) the standard deviation changes from less than a lower threshold (e.g., 0.025 Hz) to greater than a higher threshold (e.g., 0.05 Hz) or (ii) the standard deviation changes from greater than a higher threshold (e.g., 0.05 Hz) to less than a lower threshold (e.g., 0.025 Hz).

[0143] 3. Server computing device 906 adds frequency events (including, for example, the event's UTC time, location, maximum frequency jump, and standard deviation of the frequency) to the associated event queue.

[0144] 4. The server computing device 906 evaluates all frequency events in the associated event queue to identify frequency events that occur within a defined time period (e.g., 400 milliseconds) and a defined proximity (e.g., ten kilometers) to each other. In some embodiments, a minimum number of events may be required to identify associated events.

[0145] 5. The server computing device 906 stores the identified frequency events and related events in, for example, long-term storage.

[0146] 6. Server computing device 906 transmits alarm notification messages related to the detected frequency event and associated events to remote computing device 908a associated with the individual homeowner to whom the frequency event has been detected, and / or transmits notification messages related to the frequency event and associated events to remote computing devices 908 of relevant utilities or other power grid operators.

[0147] Figure 16 This is a graph showing the output signals generated by multiple different power failure detection devices during a frequency jump event. For example... Figure 16 As shown, each line in the graph represents the output signal from a different power failure detection device. Note that the output signals from each power failure detection device are very close together in this graph, making it appear as a single line. Around 19:53:00 (time t1), a frequency event occurs. The frequency signals received by server computing device 906 from each power failure detection device drop to a lower frequency and then begin to rise, indicating that a frequency event has been captured at the power failure detection device.

[0148] Neutral line loosening event

[0149] As mentioned above, a loose neutral wire is a very dangerous situation that can occur in household wiring. Typically, a loose neutral wire will break at its connection point, which can lead to abnormally high or low voltage conditions in household outlets. In some cases, current will flow to the ground through other household appliances, such as through a television to a cable TV connection. Because large currents can flow through cable TV cables or other conductors not designed to handle such large currents, this can cause arcing or the conductor to become extremely hot, burning its insulation and even damaging the surrounding environment, potentially leading to an electrical fire. In some instances, the neutral wire can be resistive. The resistance of the neutral wire is low enough to conduct some electricity, but too high to conduct electricity as well as it should. In these cases, the neutral wire can become extremely hot at locations where the resistance is higher than normal, which can also lead to a fire. To detect a loose neutral wire event, the server computing device 906 can analyze incoming power quality data as follows.

[0150] 1. Server computing device 906 retrieves historical power quality event data and historical associated event data of specific power outage detection devices 902, 910, and 912 from, for example, long-term storage. For example, as described above, the system can capture and record power quality data from power outage detection devices in a specific household over time and store the data in long-term storage to establish a historical record of power quality events associated with that household.

[0151] 2. Server computing device 906 evaluates for a single power outage detection device 902 the number and magnitude of surge events, surge jump events, and descent events recorded for the power outage detection device 902 within a predetermined time period (such as the last seven days) that are not associated with other events.

[0152] 3. If the average number of surge events is greater than a predefined threshold per day (e.g., one), or the average number of surge jump events with an amplitude greater than a predefined threshold percentage (e.g., 10%) of the nominal voltage is greater than a predefined threshold per day (e.g., ten), or the average number of descent events is greater than a predefined threshold per day (e.g., ten) (as an example condition), then the server computing device 906 generates a neutral line loosening event, and the neutral line loosening event data can be stored in, for example, long-term storage.

[0153] 4. Server computing device 906 transmits a notification message related to the neutral wire loosening event to a remote computing device 908a, for example, associated with a user. In some embodiments, the notification message may also be sent to a remote computing device 908b, for example, associated with a utility provider serving the home, so that they can identify potential repairs to improve the neutral wire loosening situation.

[0154] As an example, 17A- Figure 17C This is a graph generated from power quality data related to a neutral line loosening event captured by the power outage detection device 902. Figure 17A A graph depicting the nominal voltage RMS reading captured by the power failure detection device, such as... Figure 17A As shown, the voltage RMS value remains relatively constant over time. However, when a loose neutral wire is present, the power failure detection device 902 captures many large positive jumps in the voltage RMS value (e.g., greater than +10% of the nominal value), such as... Figure 17B As shown in the figure. Similarly, Figure 17C is a graph showing the voltage RMS readings captured by the power failure detection device 902 before and after resolving the loose neutral wire. Figure 17C As shown, the voltage RMS reading contains many large jumps before reaching the resolution point 1702, after which the voltage RMS reading returns to the nominal range without large jumps.

[0155] The following table details the number of loose neutral connections detected by the power failure detection equipment in a real-world deployment of the system described in this article:

[0156]

[0157] As shown above, in each case, the system detects one or more neutral wire loosening events associated with a specific power outage detection device and generates an alarm notification to the associated end-user equipment, thus informing the homeowner of the presence of the loose neutral wire. In each case, the loose neutral wire is subsequently verified and repaired by the utility provider. Currently, 49 cases are in progress and being resolved. The data above demonstrates the significant benefits provided by the system and method described in this paper from the perspective of quickly and accurately detecting power quality problems in a home before any potential property damage or loss of life occurs.

[0158] Recurring power quality issues

[0159] When supplying power to a household, other types of recurring power quality problems may occur (e.g., frequent surges, sudden drops, etc.). To detect these problems, the server computing device 906 can analyze the incoming power quality data as follows.

[0160] 1. Server computing device 906 retrieves historical power event data and historical associated event data of specific power failure detection devices 902, 910, and 912 from, for example, long-term storage.

[0161] 2. Server computing device 906 evaluates the number and magnitude of surge and drop events recorded for a single power outage detection device 902 within a predetermined time period (such as the last thirty days).

[0162] 3. If more than a predefined number (e.g., four) of surge events or more than a predefined number (e.g., ten) of drop events occur, the server computing device 906 generates recurring power quality problem events and can store the recurring power quality problem event data in, for example, long-term storage.

[0163] 4. Server computing device 906 transmits notification messages related to recurring power quality problem events to computing device 908a, for example, associated with a user. In some embodiments, the notification messages may also be sent to remote computing device 908b, for example, a utility provider serving a household, so that they can identify potential repairs to improve the recurring power quality problems.

[0164] Generator on / off event

[0165] The methods and systems described in this paper can also be used to detect scenarios where alternative power generation systems (such as generators installed in homes) are activated in response to power outages. To detect these scenarios, the server computing device 906 can analyze incoming power quality data as follows.

[0166] 1. Server computing device 906 retrieves historical power event data and historical associated event data of specific power failure detection devices 902, 910, and 912 from, for example, long-term storage.

[0167] 2. Server computing device 906 evaluates against a single power outage detection device 902 to determine whether any power outage events and frequency events have occurred.

[0168] 3. If a single power outage detection device 902 records a power outage event, and subsequently, within a predefined time period (e.g., sixty seconds) of the power outage event, the standard deviation of the frequency changes by more than a predefined threshold (e.g., 0.05 Hz), and the change in the standard deviation of the frequency is not associated with any external event, then the server computing device 906 generates a "generator start" event and may send a corresponding notification message to, for example, a remote computing device 908a associated with the user of the power outage detection device 902.

[0169] 4. If a single power failure detection device 902 that previously met the "generator start" event condition records a subsequent frequency event with a standard deviation change of less than 0.025 Hz, then the server computing device 906 generates a "generator stop" event and can send a corresponding notification message to, for example, a remote computing device 908a associated with the user of the power failure detection device 902.

[0170] As described above, the server computing device 106 and / or the power failure detection device 102 can be configured to generate alarm notifications, reports, maps, charts, etc., to be displayed to the user on the relevant remote computing device. Figure 18 This is a diagram displayed on a user interface of a remote computing device (e.g., a mobile phone), showing historical RMS voltage (Vrms) readings captured by the power failure detection device 102. Figure 18 As shown, Figure 1802 illustrates Vrms readings captured by the power outage detection device 102 throughout the day, and meter 1804 displays low, high, and average Vrms readings. This user interface provides an easily understandable depiction of power quality at a specific location. The user interface may also include a list 1806 of relevant power quality events, such as power outages or power surges. For example, the user interface shows a power outage occurring at 10:40 PM, represented by a yellow triangle on Figure 1802. The server computing device 106 can also generate a historical calendar view of power quality events occurring for the power outage detection device 102, such as... Figure 19As shown, users can view a month's worth of power quality events (such as power rationing, surges, and outages) to get a comprehensive picture of the overall power quality of the power grid that serves his or her home.

[0171] In conjunction with the aforementioned power quality reports and charts, server computing device 106 can also generate power quality notifications and transmit them to one or more remote computing devices. Figure 20A This is a diagram illustrating the user interface of a push notification alert sent by server computing device 106 to a remote device for display. (See diagram for example.) Figure 20A As shown, push alerts include a description of the relevant power quality event and the time the event occurred. Similarly, Figure 20B This is a diagram showing the user interface for a list of power quality notifications related to the power outage detection equipment. Figure 20C , 20D 20E is a detailed power quality event alert notification displayed to users of remote computing devices. Figure 20C It is a power surge notification that provides users with detailed information about the timing, location (e.g., which power outage detection device captured data associated with the event), and voltage readings of a surge event. Figure 20D It is a power rationing notification that provides users with detailed information about the timing, location, and voltage readings of power rationing events. Figure 20E This involves providing users with recurring power quality problem notifications, offering detailed information on the frequency and frequency of power quality issues experienced by their home electrical systems. As a result, System 100 is configured to automatically generate these alerts and quickly deliver them to relevant users, allowing them to stay up-to-date on power quality events affecting their homes or businesses.

[0172] In addition to event notification messages, the systems and methods described herein can generate maps showing the location of specific power quality events relative to each other, and enable users (e.g., customers, grid operators, utility companies) to quickly and easily determine whether a specific geographic area is experiencing the type of power quality event that needs to be addressed.

[0173] It should be understood that the server computing device 106 can generate a map that includes multiple different power outage and / or power quality events in the same geographical area. For example, in some embodiments, a user can select multiple different events (e.g., in a checkbox menu), and the server computing device 106 can use different indicators (such as different shapes, colors, etc.) to display each type of event.

[0174] The techniques described above can be implemented in digital and / or analog electronic circuit systems, or in computer hardware, firmware, software, or combinations thereof. Implementation can be as a computer program product, i.e., a computer program tangibly implemented in a machine-readable storage device for execution by or control of a data processing apparatus (e.g., a programmable processor, a computer, and / or multiple computers). The computer program can be written in any form of computer or programming language, including source code, compiled code, interpreted code, and / or machine code, and can be deployed in any form, including as a standalone program or as a subroutine, element, or other unit suitable for use in a computing environment. The computer program can be deployed to execute on one or more computers at one or more sites.

[0175] The method steps can be executed by one or more processors that execute a computer program to perform the functions of the present technology by manipulating input data and / or generating output data. The method steps can also be executed by the following, and the apparatus can be implemented as a special-purpose logic circuit system, such as an FPGA (Field-Programmable Gate Array), FPAA (Field-Programmable Analog Array), CPLD (Complex Programmable Logic Device), PSoC (Programmable System-on-Chip), ASIP (Application-Specific Instruction Set Processor), or ASIC (Application-Specific Integrated Circuit), etc. A subroutine can refer to a stored portion of a computer program and / or processor, and / or a special circuit system that implements one or more functions.

[0176] As an example, processors suitable for executing computer programs include both general-purpose microprocessors and special-purpose microprocessors, as well as any one or more processors in any type of digital or analog computer. Generally, a processor receives instructions and data from read-only memory or random access memory, or both. The basic components of a computer are a processor for executing instructions and one or more memory devices for storing instructions and / or data. Memory devices such as caches can be used for temporary data storage. Memory devices can also be used for long-term data storage. Generally, a computer also includes one or more mass storage devices (e.g., magnetic, magneto-optical, or optical disc) for storing data or operatively coupled to such mass storage devices to receive data from or transfer data to, or both. A computer may also be operatively coupled to a communication network to receive instructions and / or data from and / or transmit instructions and / or data to the network. Computer-readable storage media suitable for embodied computer program instructions and data include all forms of volatile and non-volatile memory, including, for example: semiconductor memory devices, such as DRAM, SRAM, EPROM, EEPROM, and flash memory devices; magnetic disks, such as internal hard disks or removable disks; magneto-optical disks; and optical disks, such as CDs, DVDs, HD-DVDs, and Blu-ray discs. Processors and memory can be complemented and / or integrated into dedicated logic circuitry.

[0177] To provide interaction with the user, the techniques described above can be implemented on a computer that communicates with display devices such as CRT (cathode ray tube) monitors, plasma monitors, or LCD (liquid crystal display) monitors for displaying information to the user, and with indicating devices such as keyboards, trackballs, touchpads, or motion sensors that the user can use to provide input to the computer (e.g., interact with user interface elements). Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback, such as visual feedback, auditory feedback, or tactile feedback; and input from the user can be received in any form, including sound input, voice input, and / or tactile input.

[0178] The techniques described above can be implemented in a distributed computing system that includes backend components. For example, backend components can be data servers, middleware components, and / or application servers. The techniques described above can also be implemented in a distributed computing system that includes frontend components. Frontend components can be, for example, client computers with graph user interfaces, web browsers through which users can interact with the example implementation, and / or other graph user interfaces for sending devices. The techniques described above can be implemented in any combination of such backend, middleware, or frontend components in a distributed computing system.

[0179] Components of a computing system can be interconnected via transmission media (e.g., communication networks) that can include digital or analog data communication of any form or medium. In any configuration, the transmission media can include one or more packet-based networks and / or one or more circuit-based networks. Packet-based networks can include, for example, the Internet, carrier Internet Protocol (IP) networks (e.g., local area networks (LANs), wide area networks (WANs), campus area networks (CANs), metropolitan area networks (MANs), residential area networks (HANs)), private IP networks, IP private switching extensions (IPBXs), wireless networks (e.g., radio access networks (RANs), Bluetooth, Wi-Fi, WiMAX, General Packet Radio Service (GPRS) networks, HiperLANs), and / or other packet-based networks. Circuit-based networks can include, for example, public switched telephone networks (PSTNs), legacy private switching extensions (PBXs), wireless networks (e.g., RANs, code division multiple access (CDMA) networks, time division multiple access (TDMA) networks, Global System for Mobile Communications (GSM) networks), and / or other circuit-based networks.

[0180] Information transmission over a transmission medium can be based on one or more communication protocols. Communication protocols may include, for example, Ethernet protocol, Internet Protocol (IP), Voice over IP (VoIP), peer-to-peer (P2P) protocol, Hypertext Transfer Protocol (HTTP), Session Initiation Protocol (SIP), H.323, Media Gateway Control Protocol (MGCP), Signaling System #7 (SS7), Global System for Mobile Communications (GSM), Push-to-Talk (PTT) protocol, Cellular PTT (POC) protocol, and / or other communication protocols.

[0181] Computing system devices may include, for example, computers, computers with browser devices, telephones, IP phones, mobile devices (e.g., cellular phones, smartphones, personal digital assistant (PDA) devices, laptop computers, email devices), and / or other communication devices. Browser devices include, for example, computers (e.g., desktop computers, laptop computers) with a World Wide Web browser (e.g., Microsoft® Internet Explorer® available from Microsoft Corporation, Mozilla® Firefox available from Mozilla Corporation). Mobile computing devices include, for example, iOS™-based devices (such as iPhone™ and iPad™ available from Apple Corporation) and Android™-based devices (such as Galaxy™ available from Samsung Corp., Pixel™ available from Google Corporation, and Kindle Fire™ available from Amazon Corporation).

[0182] The plural forms of include, include, and / or each are open-ended and include the listed components, and may include additional components not listed. And / or are open-ended and include one or more of the listed parts and combinations of the listed parts.

[0183] Those skilled in the art will recognize that the present invention can be embodied in other specific forms without departing from the spirit and essential characteristics of the invention. Therefore, the foregoing embodiments are to be regarded in all respects as illustrative rather than limiting of the invention described herein.

Claims

1. A system for detecting and notifying of power outages, the system comprising: A sensor device coupled to a circuit, the sensor device being configured to: Periodically send keep-alive packets to the server computing device; Detect the input signal generated by the electrical activity on the circuit; The output signal is generated based on the detected input signal; Monitor the generated output signal during each of multiple clock cycles with a predefined duration; During each clock cycle: Determine whether a rising edge appears in the generated output signal; When the rising edge occurs before a predetermined clock value in the clock cycle, or When no rising edge occurs in the clock cycle, a fault packet is transmitted to the server computing device. as well as Initiate a new clock cycle; A server computing device communicatively coupled to the sensor device, the server computing device being configured to: Receive the fault packet from the sensor device; Listen for one or more keep-alive packets from the sensor device; If no keep-alive packet is received from the sensor device within at least a defined time period after the fault packet is received, a power failure notification is transmitted to one or more remote computing devices. as well as When one or more keep-alive packets are subsequently received from the sensor device after the power outage notification has been transmitted, a power restoration notification is transmitted to the one or more remote computing devices.

2. The system as described in claim 1, characterized in that, The input signal includes an AC voltage sine wave with multiple zero-crossing points.

3. The system as described in claim 2, characterized in that, The output signal is a voltage curve having multiple rising edges corresponding to the zero-crossing point of the input signal.

4. The system as described in claim 2, characterized in that, The keep-alive group includes power quality data, which includes one or more of the following: 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 measurements of high-frequency noise amplitude.

5. The system as described in claim 1, characterized in that, Each clock cycle has a predefined duration of 9 milliseconds.

6. The system as described in claim 5, characterized in that, The predetermined clock value in the clock cycle is 8.33 milliseconds.

7. A computerized method for detecting and notifying of power outages, the method comprising: Sensor devices coupled to circuitry periodically transmit keep-alive packets to server computing devices; The sensor device detects the input signal generated by the electrical activity on the circuit; The sensor device generates an output signal based on the detected input signal; The generated output signal is monitored by the sensor device during each of a plurality of clock cycles having a predefined duration; During each clock cycle: The sensor device determines whether a rising edge appears in the generated output signal; When the rising edge occurs before a predetermined clock value in the clock cycle, or when no rising edge occurs in the clock cycle, the sensor device transmits a fault packet to the server computing device. A new clock cycle is initiated by the sensor device; The server computing device receives the fault packets from the sensor device; The server computing device listens for one or more keep-alive packets from the sensor device; If no keep-alive packet is received from the sensor device within at least a defined time period after the fault packet is received, the server computing device transmits a power failure notification to one or more remote computing devices. as well as When one or more keep-alive packets are subsequently received from the sensor device after the power outage notification has been transmitted, the server computing device transmits a power restoration notification to the one or more remote computing devices.

8. The method as described in claim 7, characterized in that, The input signal includes an AC voltage sine wave with multiple zero-crossing points.

9. The method as described in claim 8, characterized in that, The output signal is a voltage curve having multiple rising edges corresponding to the zero-crossing point of the input signal.

10. The method as described in claim 8, characterized in that, The keep-alive group includes power quality data, which includes one or more of the following: 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 measurements of high-frequency noise amplitude.

11. The method as described in claim 7, characterized in that, Each clock cycle has a predefined duration of 9 milliseconds.

12. The method as described in claim 11, characterized in that, The predetermined clock value in the clock cycle is 8.33 milliseconds.

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