System and method for intelligent event waveform analysis

Abstract

A method of analyzing an electrical energy event in an electrical power system includes monitoring at least one of voltage and current signals in the system; identifying a power event in the system based on at least one of the monitored voltage and current signals; in response to identifying the power event, capturing a waveform of at least one of the monitored voltage and current signals from a first time period before a start of the identified power event to a second time period after an end of the identified power event; determining energy-related information from the pre-event measurements and post-event measurements using the captured waveforms; identifying additional information associated with the identified electrical energy event by comparing the energy-related information determined from the pre-event and post-event measurements; performing an action affecting a component in the system, providing additional feasible information to the event report or providing the extracted signal to the automatic event analysis system, the method further comprising determining a cause of the identified electrical energy event according to the additional information; or determining the influence of the identified power event on equipment in the system.

Description

[0001] This application is a divisional application of the invention patent application with the application date of April 4, 2019, application number 201980030230.3, and invention name “System and method for intelligent event waveform analysis”.

[0002] CROSS-REFERENCE TO RELATED APPLICATIONS

[0003] This application claims priority to U.S. Provisional Application Serial No. 62 / 652,888 filed on April 4, 2018, U.S. Provisional Application Serial No. 62 / 785,297 filed on December 27, 2018, and U.S. Provisional Application Serial No. 62 / 788,392 filed on January 4, 2019, the entire contents of which are incorporated herein by reference. Technical Field

[0004] The present disclosure generally relates to intelligent event waveform capture (WFC) analysis in automated control and metering environments. Background Art

[0005] The changing world of energy makes it increasingly challenging to optimize power reliability, energy costs, and operational efficiency in critical power environments such as hospitals, data centers, airports, and manufacturing facilities. As utility grids become more dynamic, facility distribution systems become more complex and more sensitive to power quality issues threatening the stability of the network due to the increase in electronic control devices. Competitive pressures and environmental regulations are driving expectations for energy efficiency and business sustainability higher than ever before. Addressing these challenges requires new digital tools designed to respond faster to opportunities and risks related to electrical / power system reliability and operational stability.

[0006] Power quality disturbances are a leading cause of unexpected business downtime and equipment malfunction / damage / failure. According to some estimates, 30-40% of business downtime is caused by power quality disturbances, and power quality issues account for approximately 4% of a company's annual revenue. Examples of adverse effects on equipment that can be attributed to power quality disturbances include overheating of equipment components (e.g., motors, capacitors, cables, transformers, etc.), accelerated wear and tear, premature aging of equipment components, malfunctions and misoperation, and erroneous circuit breaker or relay operation.

[0007] The economic impacts of power quality disturbances can include increased energy bills, additional financial penalties (e.g., penalties due to power outages), and potential adverse effects on the environment (e.g., increased carbon footprint). Power quality disturbances may also adversely lead to increased demand-related charges, increased electrical / power system losses, and increased voltage drops. Three examples of areas affected by power quality disturbances include: uptime, asset condition, and energy efficiency. For example, expected or unexpected outages of electrical facilities due to voltage sags, interruptions, and / or undervoltage / overvoltage conditions may affect system uptime. In addition, nuisance tripping of circuits caused by harmonics, voltage swells, or transients may also result in reduced uptime. Assets (e.g., cables, transformers, capacitor banks, etc.) may be adversely affected by power quality disturbances or conditions. For example, equipment overheating, unexpected changes in design features, and / or reduced service life are just a few of the effects caused by power quality anomalies. Finally, the efficient use of energy is also affected by power quality disturbances.

[0008] According to a specific example, capacitor banks may be affected by power quality disturbances (e.g., harmonics), which are characterized by steady-state distortions of voltage and / or current signals. Non-linear power loads from electric arc furnaces (EAF), electric railways, and thyristor-based voltage and frequency correction equipment have become sources of primary harmonics in the power grid. These systems inject large amounts of harmonic currents into the electrical / power system, causing distortion of the fundamental current signal in the grid. Harmonics may adversely affect the normal operation of capacitor banks in a variety of ways (e.g., increasing power losses, generating harmonic resonances, increasing harmonic currents, and reducing the service life of capacitor banks through additional heating).

[0009] Proper interpretation of power quality data can provide businesses and energy providers with the ability to limit the adverse effects caused by power quality disturbances. Energy procurement managers can use power quality data to identify and avoid penalties or to modify / update energy contracts. Similarly, maintenance engineers can use power quality data to properly diagnose equipment problems, improve root cause analysis and reduce equipment downtime.

[0010] It may not be practical to collect and store all power quality data from an electrical / power system. Power quality data collected during a power quality event or other power problem may not be sufficient to provide an adequate explanation of the power quality problem on the electrical / power system, which is important for maintaining and improving the performance of the electrical system. Summary of the invention

[0011] According to an exemplary embodiment, a method and system are provided to analyze an energy event in an electric power system, which can be performed using at least an intelligent electronic device (IED) including a processor, a sensor, and a memory. In the method and system, voltage and / or current signals on the electric power system are monitored. An energy event in an electrical / power system is identified based on at least one of the monitored voltages and / or currents. In response to identifying an energy event, waveform data of at least one of the monitored voltages and / or currents is captured and stored. Energy-related information is determined (e.g., identified, measured, calculated, derived, used, and / or extracted) based on pre-event measurements using the captured waveform. Energy-related information is also determined (e.g., identified, measured, calculated, derived, used, and / or extracted) using the captured waveform during the event and based on post-event measurements. Energy-related information may include (multiple) energy-related parameters, (multiple) signals, (multiple) indicators, (multiple) states, and / or other information. Additional information associated with an electrical energy event is identified, calculated, derived, and / or determined by comparing (a) energy-related information determined based on pre-event measurements and (b) energy-related information determined based on post-event measurements. In some cases, pre-event information can be compared with data during the event. In addition, data acquired during the event can be compared with data acquired at the end of the event. An IED can be a device or system (e.g., a meter, a drive, a UPS (Uninterrupted Power Suppl), a circuit breaker, a relay, other electrical equipment associated with or connected to an electrical / power system, or other components and / or devices capable of measuring and capturing energy signals).

[0012] The power event may be a power quality event. The additional information may include, for example, evidence of capacitor bank switching in the electrical / power system or load loss in the electrical / power system. The system and method may also include determining at least one cause of the power event based on the additional information, determining an effect of the power event on equipment in the electrical / power system, or performing an action that affects at least one component in the electrical / power system based on the additional information. The at least one component may include equipment in the electrical / power system. The IED may be coupled to the electrical / power system equipment.

[0013] The captured waveform can be a waveform of the monitored voltage and / or current signal from a first time period before the identified power event begins to a second time period after the identified power event ends. Power can be derived from, for example, the voltage and current. The first time period or the second time period can be adjusted (e.g., dynamically adjustable) based on the condition of the electrical / power system (e.g., a variable duration of a power quality event).

[0014] Additional information may also include a phase shift (e.g., also referred to as a phase shift) of the monitored voltage and / or current that satisfies a phase shift threshold condition. Additional information may also include identification of one or more duration changes in the monitored voltage and / or current by determining the duration of each half-cycle of the waveform from the captured waveform.

[0015] According to another exemplary embodiment, a method and system for creating an energy event profile for an electrical / power system using an intelligent electronic device (IED) including at least a processor, a sensor, and a memory is provided. In the method and system, the voltage and / or current on the electrical / power system are monitored. During normal or typical operation of the electrical / power system, for example, at an expected predetermined time period or a random time period, the waveform of the monitored voltage and / or current. When the captured waveform represents an unknown energy event profile for normal operation of the electrical / power system, a new energy event profile for normal or typical operation is created for the captured waveform. The digital repository is updated with the new energy event profile for normal or typical operation.

[0016] According to an exemplary embodiment, the present disclosure contemplates a system for intelligent event analysis. The consequences of a disturbance can be determined. For example, disturbance data can be collected for a selected portion of a disturbance event (e.g., before and / or after the disturbance). A set of measurements can be iteratively calculated at a control node based on the collected disturbance data. The iterative calculation can be monitored for a change threshold. When the iterative calculation meets the change threshold, the iterative calculation can be associated with an impact criterion that is used to determine the consequences of the disturbance.

[0017] According to another exemplary embodiment, analysis of waveform data is typically focused on the disturbance itself; however, there is pre-event / post-event non-disturbance data that is typically ignored. For example, pre-event / period / post-event features of a disturbance waveform capture (WFC) may be analyzed to determine whether a capacitor bank has been energized (e.g., "turned on"). This determination may be based on a combination of WFC event features, changes in actual / reactive / apparent load demand, and changes in power factor. This information may also indicate the location of the IED that captured the event, either electrically / physically upstream or downstream of the capacitor bank. It will be indicated that the IED that captured the WFC is physically / electrically installed upstream of the capacitor bank. For example, a change in reactive power may indicate that a capacitor bank downstream of the IED is energized. Based on the capabilities of the IED, the IED may derive various parameters from the captured waveform(s), such as mean squared (MS) or root mean squared (RMS) values ​​of voltage, current, power, reactive power, THD, and discrete harmonics. An array (e.g., a spreadsheet) of these values ​​may be calculated based on pre-event and / or post-event data. This array can be used to enrich (e.g., tag) each event waveform with its pre / during / post-event parameters (e.g., any large waveform database). These waveform arrays can then be automatically analyzed (e.g., using attributes) to detect statistically significant changes.

[0018] According to an exemplary embodiment, a method for analyzing an electrical energy event in an electrical power system using at least one processor and a sensor is provided, the method comprising: monitoring at least one of a voltage and a current signal in the electrical power system; identifying at least one electrical energy event in the electrical power system based on at least one of the monitored voltage and current signals; in response to identifying the at least one electrical energy event, capturing a waveform of at least one of the monitored voltage and current signals from a first time period before the start of at least one identified electrical energy event to a second time period after the end of at least one identified electrical energy event; using the captured waveform to determine energy-related information based on pre-event measurements, the energy-related information determined based on the pre-event measurements including at least one of energy-related parameters, signals, indicators, states, and other information; using the captured waveform to determine energy-related information based on pre-event measurements Determine energy-related information based on post-event measurement values, wherein the energy-related information determined based on the post-event measurement values ​​includes at least one of energy-related parameters, signals, indicators, states and other information; identify and / or derive and / or calculate additional information associated with the at least one identified electrical energy event by comparing (a) energy-related information determined based on pre-event measurement values ​​and (b) energy-related information determined based on post-event measurement values; and perform at least one action affecting at least one component in the electrical power system, provide additional feasible information to the event report, or provide an extracted signal to an automated event analysis system, wherein the method further includes: determining at least one cause of the at least one identified electrical energy event based on the additional information; or determining the impact of the at least one identified electrical energy event on equipment in the electrical power system.

[0019] According to an exemplary embodiment, a system for analyzing power events in an electrical power system is provided, the system comprising: a memory; one or more sensors configured to sense at least one of voltage and current signals in the electrical power system; and one or more processors configured to: monitor at least one of the voltage and current signals using the one or more sensors; identify at least one power event in the electrical power system based on at least one of the monitored voltage and current signals; in response to identifying the at least one power event, capture a waveform of at least one of the monitored voltage and current signals from a first time period before the start of the identified power event to a second time period after the end of the identified power event; determine energy-related information based on pre-event measurements using the captured waveform, the energy-related information determined based on the pre-event measurements including energy-related parameters, signals, indicators, states, and other at least one of the information; determining energy-related information based on post-event measurements using captured waveforms, the energy-related information determined based on post-event measurements including at least one of energy-related parameters, signals, indicators, states and other information; identifying and / or deriving and / or calculating additional information associated with at least one identified electrical energy event by comparing (a) energy-related information determined based on pre-event measurements and (b) energy-related information determined based on post-event measurements; and performing at least one action affecting at least one component in the electrical power system, providing additional actionable information to an event report, or providing an extracted signal to an automated event analysis system, wherein the one or more processors are further configured to: determine at least one cause of the at least one identified electrical energy event based on the additional information; or determine the impact of the at least one identified electrical energy event on equipment in the electrical power system.

[0020] According to an exemplary embodiment, a tangible computer medium storing computer executable code is provided, and when the computer executable code is executed by a processor, it is configured to implement a method for analyzing an electrical energy event in an electrical power system, the method comprising: monitoring at least one of a voltage and a current signal in the electrical power system; identifying at least one electrical energy event in the electrical power system based on at least one of the monitored voltage and current signals; in response to identifying the electrical energy event, capturing a waveform of at least one of the monitored voltage and current signals from a first time period before the start of the identified electrical energy event to a second time period after the end of the identified electrical energy event; using the captured waveform to determine energy-related information based on pre-event measurements, the energy-related information determined based on the pre-event measurements including at least one of energy-related parameters, signals, indicators, states, and other information One; using captured waveforms to determine energy-related information based on post-event measurement values, the energy-related information determined based on the post-event measurement values ​​includes at least one of energy-related parameters, signals, indicators, states and other information; by comparing (a) energy-related information determined based on pre-event measurement values ​​and (b) energy-related information determined based on post-event measurement values, identifying and / or deriving and / or calculating additional information associated with at least one identified electrical energy event; and performing at least one action affecting at least one component in the electrical power system, providing additional feasible information to the event report, or providing an extracted signal to an automated event analysis system, wherein the method also includes: determining at least one cause of the at least one identified electrical energy event based on the additional information; or determining the impact of the at least one identified electrical energy event on equipment in the electrical power system.

[0021] Additional objects and advantages will be explained in part in the following description, and in part will be obvious from the description, or can be understood by the practice of the present disclosure and / or claims. At least some of these objects and advantages can be realized and obtained by the elements and combinations particularly pointed out in the appended claims.

[0022] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as disclosed or claimed. The claims should be given their full scope, including equivalents. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The description of various example embodiments is explained in conjunction with the accompanying drawings.

[0024] FIG. 1 is a schematic diagram of an exemplary network configured to intelligently analyze power events on an electrical / power system according to an exemplary embodiment of the present disclosure.

[0025] 2 illustrates example waveforms and calculated measurements of different voltage phases monitored on a multi-phase electrical / power system (eg, a three-phase electrical / power system) according to an exemplary embodiment of the present disclosure.

[0026] 3 illustrates a flow chart of an exemplary process by which waveforms of monitored electrical characteristic(s) on an electrical / power system are captured and analyzed, and actions are taken based on the resulting waveform analysis, in accordance with an exemplary embodiment of the present disclosure.

[0027] 4A , 4B, and 4C illustrate example waveforms of monitored and captured voltages of different phases A, B, and C of an electrical / power system according to an exemplary embodiment of the present disclosure.

[0028] 5A illustrates example waveforms of voltage and current monitored and captured for different phases A, B, and C of an electrical / power system, provided for comparison with each other for waveform analysis, according to an exemplary embodiment of the present disclosure.

[0029] 5B illustrates another example of current waveforms of current monitored and captured for different phases A, B, and C of an electrical / power system with pre-event, event, and post-event measurement data according to an exemplary embodiment of the present disclosure.

[0030] Figures 6 and 7 illustrate an exemplary process according to an exemplary embodiment of the present disclosure, by which (multiple) electrical characteristics on an electrical / power system are monitored to identify and create event profiles of normal operation on the electrical / power system, and the electrical energy event profiles are stored in a digital repository (e.g., a library).

[0031] 8A , 8B, and 8C illustrate a flow chart of an exemplary process by which measurement data (eg, waveform data) is analyzed to adjust pre-event and / or post-event capture periods according to an exemplary embodiment of the present disclosure.

[0032] 9A and 9B illustrate a flow chart of an exemplary process by which the pre-event and post-event time periods may be calculated for FIG. 8C , according to an exemplary embodiment of the present disclosure.

[0033] 10 illustrates a block diagram of example components of a general purpose computer system, such as an intelligent electronic device (IED) or other computer system according to an example embodiment of the present disclosure.

[0034] FIG. 11 provides a table listing examples of additional information that may be determined by evaluating pre-event and post-event measurement data according to various exemplary embodiments of the present disclosure. DETAILED DESCRIPTION

[0035] Provided are methods and systems for enhancing event analysis by monitoring, capturing, and analyzing measurement data, including pre-event, event, and post-event data representing signal waveforms of voltage and / or current signals or other measurable and / or derivable electrical characteristics monitored on an electrical / power system when an event is detected. Pre-event and post-event measurement data can be captured over a duration or time period (e.g., half, one, one and a half, two or more cycles), which is fixed or changed based on, for example, attributes monitored on the electrical / power system, user input, or system commands from another network node. The captured measurement data (e.g., pre-event waveforms (multiple) before the event is detected, event waveforms (multiple) during the event, and post-event waveforms (multiple) after the event endpoint is detected) can be analyzed for phase shifts, duration changes, differences in amplitude or phase angle, or other anomalies within one or more power line phases to provide additional information related to the detected event.

[0036] Methods and systems are also provided for identifying, creating, and storing new electrical energy event profiles for normal operation (e.g., electrical energy events representative of normal operation) by capturing and analyzing measured values ​​and / or derived energy data (e.g., waveforms of voltage and / or current signals or other measurable and / or derivable electrical characteristics monitored on the electrical / power system) during normal operation of the electrical / power system.

[0037] These and other example features of the present disclosure will be described in more detail below with reference to the accompanying drawings.

[0038] I. Network system architecture

[0039] Referring to FIG. 1 , a schematic diagram of an exemplary network system architecture configured to perform intelligent event analysis, etc. at (multiple) network nodes is depicted. The architecture includes one or more network nodes 126, user devices 114 and 116 to monitor and control equipment or other devices 102, 104 and 106 of facilities 108, 110 and 112. The architecture also includes an electrical / power system that includes (multiple) power generation nodes 122 to supply power to facilities 108, 110 and 112 through a utility's distribution network (e.g., grids 118 and 120) and facilities. Facilities 108, 110 and 112 may be automated industrial facilities or include automated industrial equipment. Systems and devices in the network architecture may communicate on a communication network 124 using a local area network (LAN), a wide area network (WAN) or an interconnected network (including the Internet). The communication network 124 may be a wired and / or wireless network that carries network data between network nodes using, for example, physical and / or wireless data links.

[0040] Each network node 126 may include a computer system (e.g., an intelligent electronic device (IED)) to sense, monitor, capture, and analyze power-related data on the electrical / power system. According to various embodiments, the IED may capture a signal waveform representing a voltage, current, power, or other measurable electrical characteristic on the electrical / power system, create an electrical energy event profile, perform event analysis to identify an electrical energy event and additional information using waveforms including pre-event / during-event / post-event waveforms, and perform other operations as part of the waveform capture and event analysis described herein. The IED may be an intelligent device (e.g., an intelligent power meter or other power equipment, or an intelligent device incorporated into or associated with a power meter or other power equipment on the electrical / power system). The architecture may include multiple IEDs arranged at different upstream and downstream locations on the electrical / power system in a hierarchical or layered relationship to monitor and share power-related information (e.g., measurement data, derived data, event data and additional information, results of event analysis, event profiles, etc.) at any desired location along the electrical / power system (including locations along the power grid, locations between utilities and facilities, and locations within facilities). Example components of a computer system are further described below with reference to FIG. 10 .

[0041] II. Event Analysis and Waveform Capture

[0042] 1. Before and after the event

[0043] Power events, such as power quality (PQ) events, can be detected and classified by monitoring, identifying, capturing and analyzing measured and / or derived data (e.g., waveforms of voltage and / or current signals on an electrical / power system or other measurable and / or derivable electrical characteristics). These operations can be performed on a computer system (e.g., a smart meter or other intelligent electronic device (IED)). When an event / event is detected to be triggered, such as when a threshold, rule or condition is met or violated, the measurement data is captured. These set points can be derived from specifications, local or utility-related regulations, or from best practices, industry-specific standards or recommendations, or industry sector-specific levels. (Multiple) waveforms (e.g., event waveforms) from the start to the end of the event can be captured and analyzed to identify relevant representative parameters, elements and / or statistical / analysis dimensions, such as the amplitude of electrical characteristics, harmonics, power factor, duration of the event, event severity, disturbance direction detection (DDD), or other event characteristics. Event severity can be derived by calculating, for example, "intensity * duration" or any similar or more complex metric that can be representative of an event or useful for later calculations and analysis. For example, the DDD can be displayed at the level of each meter if the event most likely originated upstream or downstream of the meter. Data of the detected event(s) can be reported in event reports to other computer systems (e.g., other IEDs) that are part of the monitoring system in the network system architecture.

[0044] Measurement data captured during an event (e.g., a time period from the start to the end of a detected event or during an event) may not be sufficient to fully understand the detected event (e.g., the circumstances surrounding the event, including potential causes of the event). To improve event analysis, measurement data of the pre-event and post-event states of the electrical / power system may also be captured and analyzed to provide additional information and context for the detected event. FIG2 shows an example of a captured waveform (e.g., a measured or calculated waveform) of a monitored voltage on a multi-phase electrical / power system. Once the pre-event, event, and post-event measurement data are captured, the attributes of the pre-event, event, and post-event data may be evaluated / analyzed to obtain additional information about the event, which may result in action being taken, such as by a power meter, protective device, or other system. In addition, the captured, measured, and derived data associated with the detected event (e.g., pre-event, event, and post-event) may be tagged and reported in an event report, which is transmitted to other systems or devices or the cloud.

[0045] In various example embodiments, electrical / power system measurements can be calculated from steady-state portions of waveforms before and after the event that triggers the capture. Pre-event data can be compared with post-event data to extract additional information about the event (e.g., evidence or metadata of capacitor bank switching, loss or increase of load or load type, other changes in the electrical / power system, or other information). Data from steady-state portions of waveforms before and after an electrical energy event can provide additional information that can help determine (a) the cause of the event, and (b) the impact on equipment on the electrical / power system. For example, pre-event and post-event data can be isolated, and additional data can be derived (e.g., voltage / current / power RMS can be calculated per phase or per aggregate phase, and each phase can include relevant data such as phase angle, phase shift, line or phase voltage, line or phase current, power factor, power, single harmonics, and other features). Statistical analysis can also be performed on changes or variations in measured values ​​or calculated data from before to after the event. Significant changes in one or more measurements may be associated with an impact on equipment on the electrical / power system (e.g., operation of a capacitor bank or loss or increase of load or load type following an event or other change in the electrical / power system). Rules such as thresholds or conditions may be used to determine the significance of the change. The determined causes and effects are additional descriptive information that may be stored as additional metadata about the event or electrical / power system and may be useful for higher level analysis.

[0046] Various representative parameters, features, and / or elements of the pre-event and post-event states may be measured or calculated (e.g., phase shift (or phase change), magnitude of electrical characteristics, real power / active power / reactive power changes, harmonics, power factor, duration of the event, or other pre-event / post-event parameters). Pre-event and post-event features may be compared to ascertain additional information about or surrounding the detected event. For example, it is possible to ascertain from the pre-event and post-event information (combined with other known or monitored information such as system and component information) the following: (i) whether a system component was energized or de-energized, (ii) which reactive characteristic (e.g., capacitive or inductive) of the load(s) was energized or de-energized when the power factor changed, (iii) whether the load was stable when the capacitor bank was energized or de-energized, (iv) whether a voltage phase shift that occurred indicates a potential change in power source (e.g., between the utility and the generator), (v) a change in load balance, and (vi) a change in discrete or total harmonic distortion consistent with load energization or de-energization (i.e., this can help identify the electronic power supply that generated the motor protection trip / disturbance). Additional examples of analyses that can be performed include the following:

[0047] (1) If the power factor before and after the event is different (for example, V aand I a If there is a change in the phase angle between the capacitor bank and the load, this situation can indicate that the capacitor bank is energized or de-energized. This inference can be confirmed by waveform analysis. Alternatively, this situation can indicate some information about the type of load added or removed from the system.

[0048] (2) If there is a change in the total current or the current per phase (e.g., between pre-event and post-event), this situation can indicate that load has been added or removed from the system. This can indicate that the protection device removed a certain percentage of the load due to a downstream fault. In addition, the analysis can take into account other information (e.g., the location of certain components on the electrical / power system). The above are just examples of rich (e.g., additional) information that can be obtained by evaluating pre-event, event, and post-event data. Other examples are provided in the table of Figure 11.

[0049] 3 shows a flow chart of an example process 300 by which measurement data of monitored electrical characteristics on an electrical / power system (such as voltage and current waveforms) is captured and analyzed, and actions are taken based on the resulting waveform analysis (e.g., measurement, derivation, and calculation). By way of example, the process 300 will be described below with reference to a computer system, such as an IED configured to monitor measurable electrical characteristics of an electrical / power system.

[0050] At reference 305, the IED identifies an electrical energy event in the electrical / power system while monitoring the electrical / power system. At reference 310, the IED determines the occurrence time of the identification of (multiple) electrical energy events. At reference 315, the IED captures measurement data (e.g., (multiple) waveforms of voltage and / or current signals of the electrical / power system monitored by the IED or other measurable and / or derivable electrical characteristics). The electrical measurement data may include data for each power phase of the electrical / power system (e.g., a single-phase or multi-phase electrical / power system). At reference 320, the IED uses the captured (multiple) waveforms to determine timestamps for pre-event and post-event information. The event duration can be determined based on the pre-event and post-event timestamps (e.g., the pre-event timestamp minus the post-event timestamp can be equal to the event duration).

[0051] At reference 325, the IED extracts and calculates energy-related information, such as (multiple) energy-related signals (e.g., voltage and current signals), from pre-event measurements from the captured waveform(s). At reference 328, the IED extracts and calculates energy-related information, such as (multiple) energy-related signals, from event measurements (e.g., during time) from the captured waveform(s). At reference 330, the IED extracts and calculates (multiple) energy-related signals from post-event measurements from the captured waveform(s). At reference 335, the IED extracts and calculates additional information by comparing pre-event, event, and post-event calculations, derivations, and / or measurements. Examples of such calculations, derivations, and / or measurements may include, for example, phase shifts (e.g., per half cycle), amplitude changes, power factor changes, and / or other relevant power features that can be determined from the waveform(s) within the constraints of the IED that ascertains the calculations, derivations, and / or measurements. For clarity, some or all calculations may be performed in a software application, cloud-based application, gateway, and / or other location / device / system remote from the IED that extracts the energy-related signal(s).

[0052] Following reference 335 , the IED may perform an action affecting at least one component of the electrical / power system at reference 340 , provide additional actionable information to an event report at reference 345 , or provide the extracted signal(s) to an automated event analysis system at reference 350 .

[0053] Although process 300 is described with reference to an IED, various operations may be distributed and performed across multiple different computer systems that communicate with each other (e.g., via a network). Various operations in process 300 (e.g., operations at references 325, 328, and 330) may be performed serially or in parallel. In addition, in addition to (multiple) signals, energy-related information may include (multiple) energy-related parameters, (multiple) indicators, (multiple) states, and / or other information, which may be determined based on pre-event, event, and post-event measurements and used to determine additional information associated with the electrical energy event. Some examples may include AC and / or DC voltage signals, AC and / or DC current signals, power, distortion (e.g., harmonics / interharmonics), DC offset, noise, discrete phase data (e.g., voltage and / or current phase), frequency, phase angle, the status or occurrence of load loss (e.g., yes or no), which may reflect that something was added to or removed from the system during the event, percentage of load loss, power factor change, change in steady-state voltage / current shape (e.g., harmonic and interharmonic changes), and / or other measured and derived information.

[0054] An example of measurement and calculation of waveforms of a multi-phase electrical / power system performed by an IED and / or other computer system is described with reference to FIG. 4A, FIG. 4B and FIG. 4C and FIG. 5A. FIG. 4A, FIG. 4B and FIG. 4C show example measurement data in waveform form of voltages monitored and captured for different phases A, B and C of an electrical / power system. As shown, the waveforms captured on each phase A, B and C include pre-event, event and post-event measurement data. In this example, each of the voltage waveforms can be analyzed to determine additional information about detected events on the electrical / power system by comparing features that can be distinguished from pre-event and post-event measurement data (e.g., phase shift). For example, phase shift analysis can include using the zero-crossing of the signal to calculate the duration of each half-cycle of the waveform to determine whether there is any significant change in the duration of the half-cycle (e.g., comparing the change in the duration of the waveform from a certain half-cycle or the nth half-cycle (where n is an integer 1, 2, ...) to the next half-cycle). If desired, a graph (or data) of duration versus half-cycle can be calculated / derived / generated for each waveform to compare and / or visualize the change in duration across the half-cycle of the waveform. As shown in Figures 4A, 4B, and 4C, initial determinations of significant changes in duration are highlighted on the waveforms of phases A, B, and C (see, e.g., arrows).

[0055] As shown in FIG. 5A , the voltage waveforms can be overlapped with each other, and the most significant duration changes can be identified (for example, if the duration changes occur in the same time period in two or more phases, or other rules or conditions are used). This may be a way to filter out less significant duration changes. In this example, there are three significant duration changes. In the overlapping voltage waveforms, the first occurs at the beginning of the event, the second occurs near the middle of the event, and the third occurs at the end of the event. As further shown in FIG. 5A , the current waveform of a given event can also be analyzed in a similar manner to the voltage and can also be overlapped. The time period with significant duration changes is also highlighted on the superimposed current waveform of each phase, and the time period of interest can be identified to evaluate where changes may occur. Based on the comparison of some of the representative parameters, features and / or elements measured, derived and / or calculated from the voltage and current waveforms (including pre-event, event and post-event measurements, such as changes in amplitude, phase angle, half-cycle duration, power factor and other relevant electrical characteristics), (in this example) it can be identified that a short circuit occurred during the first highlighted time period, a significant neutral current was generated from the second highlighted time period during the event, and a trip occurred downstream during the third highlighted time period.

[0056] The above is only an example of waveform analysis that considers pre-event, event, and post-event measurement data of voltage and / or current signals. FIG5B shows another waveform example of monitored current for different phases A, B, and C of the electrical / power system, where thirty-two (32) measurement data can be analyzed. It should be understood that additional information can be obtained by analyzing the waveforms, parameters, and / or representative features (or "statistical / analytical dimensions" in data science terms) of one or more voltage and / or current signals or other measurable and / or derivable electrical characteristics, including changes in electrical characteristics between pre-event, event, and post-event on the electrical / power system.

[0057] According to various example embodiments, the capture periods before and after a detected event may also be predefined or changed so that pre-event and post-event measurement data (e.g., waveforms) are captured within a sufficient period (e.g., half a cycle, one cycle, one half a cycle, two cycles, etc.) to avoid missing relevant data. This can be achieved by determining a stable series of points in the measurement data before and after the event using (e.g.) the RMS value of the waveform. In this way, relevant data reflecting the changes in the waveform before and after the event is captured. The capture periods before, after, and after the event may be automatically adjusted in the IED or other remote computer system. The desired period of measurement data (e.g., (multiple) waveforms) may be obtained from a real-time system, a memory system, a buffer, or other memory storing the monitored electrical characteristics, parameters, and / or features (or statistical analysis elements and / or dimensions).

[0058] For example, the end of an event associated with a voltage signal can be tracked, and the effects subside, so that several cycles of the new normal "steady-state" behavior can be captured. Sufficient post-event measurement data is captured to extract all relevant signals. The steady state of the sampling points (e.g., a pseudo-consistent series of data points) before and after the detected event can provide a reference to determine the appropriate capture period for the pre-event and post-event measurement data. In electrical / power systems, measured, calculated and / or derived electrical characteristics can be extrapolated. Therefore, missing data can be extrapolated with different degrees of statistical and / or rule-based confidence. The characteristics of adjusting / correcting the capture period for detected events can be automatically implemented in the IED or other computer system (e.g., smart meter).

[0059] 2. Example

[0060] Additional discussion of examples including exemplary scenarios is provided below to explain the usefulness of various features described herein. These examples may be discussed with reference to IEDs (eg, smart meters, circuit breakers, or other equipment or IEDs on an electrical / power system).

[0061] For example, the power meter can use a high-speed data buffer to process and discretely measure, derive, record and store electrical characteristics on the electrical / power system, such as voltage and / or current signals or other measurable and / or derivable electrical characteristics. The power meter can then retain only the measurement data (e.g., (multiple) waveforms) captured based on event detection. Absolute thresholds (e.g., absolute and / or relative voltages) can be used to detect events. The threshold can be adjusted and changed based on received data or other factors (e.g., a recognized standard relative to the nominal voltage, or a location setting that can be changed based on, for example, a key application that needs to be monitored). A location requiring increased sensitivity can use a threshold closer to the nominal voltage. Less stringent locations may allow the threshold to be set away from the nominal voltage. For example, for an insensitive process, the threshold can be set close to 25%, rather than triggered at 10%, because 10% may have a potential risk of impact. Therefore, the power meter can be selectively configured to discretely measure, derive and / or record and capture waveforms based on defined thresholds, triggers and / or other parameters. The measured voltage and / or current signals (or derived parameters including RMS) can be evaluated against thresholds to detect the start of an event and initiate a waveform capture operation. This approach can be applied at different levels / layers, where thresholds are applied at different levels / layers and can be an extension of alarm events.

[0062] (Multiple) power meters can serve as collection modules for collecting data points (e.g., power event data and additional information) and can be provided at different locations, levels, areas or layers (e.g., at a data center, a hospital subsystem, a room level, a building level, a system level) along the power distribution system. The power meter can collect reporting data from one or more locations, levels, areas or layers. The collected information, which can be further processed, can be sent to a computer or control network node. The power meter itself can also be configured to act as a computing or control network node and can be directly connected to the cloud. In a distributed network system architecture, analysis of pre-event, event and post-event characteristics can occur at the meter, and calculation and analysis can occur at any layer (e.g., at the meter, at the edge device, in the box, at the network monitoring level (e.g., software that tracks real-time power on the system or in the cloud)), or various operations can be distributed between different systems and devices in the network.

[0063] The analysis of each waveform can be selectively localized. For example, analysis, interpretation and / or models implemented at the system level can be communicated to the IED for local implementation. A digital repository can collect this information and categorize, store and / or utilize it in some manner. A library and / or digital repository can be provided for smart alarms and thresholds. Waveform analysis can eliminate the dimensions of what happened before the event, during the event, and after the event. All three can be compared in the digital repository and can also be compared against each other. When a change is detected (e.g., what happened before the event, during the event, and after the event), the signal between what was before the event and what was / what happened after the event is compared to determine additional information related to the detected event (e.g., actions surrounding the event, such as source changes, load loss or power outage upstream or downstream, short circuits, reactive or inductive loads, etc.).

[0064] Power meters can be used to capture waveforms at different locations, levels, zones, or layers of a site (e.g., a hospital or university campus). For example, a main power meter can reflect a utility service meter, and other IEDs can be placed to capture and report data at key locations, including captured waveforms. The data provided by these power meters (e.g., waveforms captured around a specific time period or (multiple) events) can be analyzed together to provide a more detailed picture of the state of the electrical / power system and any detected events. The measured, captured, derived, and / or analyzed data can also be tagged by the power meter to facilitate its processing (e.g., part of a phase, type of associated waveform, voltage, current, power, reactive power, etc.), and also mapped to a specific location in the electrical hierarchy. Tags can also be used to classify priorities, locations (e.g., local, regional, or system), and other relevant information. Power meters can be part of a larger monitoring system that can be implemented through the cloud to provide event and alarm reports by analyzing data from power meters and other cloud services. The data collected from the meter may, for example, be provided to a cloud or other network component for further processing, which may require pooling, correlating, and analyzing the data, and reporting the data to a user or other system. Updates may be pushed to the power meter for use in performing analysis of the measured data or data calculated therefrom.

[0065] It should be noted that the power meter is provided only as an example of an intelligent electronic device (IED), which can be configured to implement the operations described herein. Other computer systems or devices can also be configured to implement the operations described herein. For example, as used herein, an IED can be a computing electronic device optimized to perform a specific function or a set of functions. Examples of IEDs can include smart utility meters, power quality meters, and other metering devices. IEDs can also be embedded in variable speed drives (VSDs), uninterruptible power supplies (UPSs), circuit breakers, relays, transformers, or any other electrical devices. IEDs can be used to perform monitoring and control functions in various facilities. These facilities can include utility systems, industrial facilities, warehouses, office buildings or other commercial complexes, campus facilities, computing hosting centers, data centers, distribution networks, etc. For example, in the case where the IED is a power monitoring device, it can be coupled to a distribution system (or installed in a distribution system) and configured to sense and store data of electrical parameters of the distribution system as representations of operating characteristics (e.g., voltage, current, waveform distortion, power, etc.). Users can analyze these parameters and characteristics to assess potential performance, reliability, or power quality related issues. An IED may include at least one controller (which, in some IEDs, may be configured to run one or more applications simultaneously, serially, or both simultaneously and serially), firmware, memory, communication interfaces, and connectors that connect the IED to external systems, devices, and / or components of any voltage level, configuration, and / or type (e.g., AC, DC). At least some aspects of the monitoring and control functionality of the IED may be embodied in a computer program accessible by the IED.

[0066] In some embodiments, the term "IED" as used herein may refer to a hierarchy of IEDs operating in parallel and / or in series. For example, an IED may correspond to a hierarchy of energy meters, power meters, and / or other types of resource meters. The hierarchy may include a tree-based hierarchy, such as a binary tree, a tree with one or more child nodes descending from each parent node or multiple parent nodes, or a combination thereof, where each node represents a specific IED. In some cases, the hierarchy of IEDs may share data or hardware resources and may execute shared software.

[0067] III. Event Profile Creation

[0068] According to another embodiment, a profile library of normal operation and / or typical power events can be constructed by capturing and analyzing measurement data (e.g., waveforms) of voltage and / or current signals or other measurable / derivable electrical characteristics during normal operation of the electrical / power system (e.g., when no power or disturbance events are detected). For example, waveforms can be captured periodically, which are not associated with or triggered by any event, to show behavior on each dimension / measurement, thereby identifying all encountered and different power quality (PQ) profiles over a longer learning period. This is a method of building a site- and / or meter-specific library of "PQ profiles" where they occur.

[0069] Once learned and analyzed (e.g., sent to a meter or driven by a system), these PQ profiles can be used to trigger new waveform captures on new possible profiles. For example, if the actual voltage and / or current waveform deviates from all known profiles in the digital repository, a new steady-state profile can be detected. Therefore, it is not necessary to continuously capture all measurements, derivations, and values. In addition, each new profile is automatically analyzed to perform a classification of this new steady state. Any new profile can be used to perform risk or impact analysis and enable, for example, predictive and preventive analysis and services. New profiles can also be analyzed relative to other profiles that are related in time or dimension to predict whether the electrical / power system is moving slowly or quickly towards an abnormal operating state (e.g., an electrical energy event).

[0070] 6 and 7 illustrate an exemplary process 600 by which electrical characteristics (multiple) on an electrical / power system are monitored to identify and create an event profile of normal operation on the electrical / power system, and the power event profile is stored in a digital repository. By way of example, process 600 will be described below with reference to a computer system (e.g., an IED) that is configured to monitor and measure electrical characteristics (multiple) of an electrical / power system.

[0071] 6 , the IED begins a learning period at reference 605. At reference 610, the IED captures voltage and / or current signals or other measurable and / or derivable electrical characteristics during normal operation of the electrical / power system (e.g., no power events are detected or associated).

[0072] At reference 615, the IED uses the captured waveforms to identify a "normal" power event profile, such as power quality (PQ) profile(s), for the electrical / power system. The event power profiles represent typical power events on the electrical / power system.

[0073] At reference 620, the IED builds a digital repository of "typical power event profiles" (eg, a digital repository of power quality profiles that includes the identified typical power quality profile(s)).

[0074] At reference 625, the IED determines whether to continue the learning process. If so, process 600 returns to reference 610. Otherwise, process 600 proceeds to reference 330, as shown in FIG7. At reference 630, during normal operation of the electrical / power system, when no power event is detected or linked to a power event, the IED captures voltage and / or current signals or other measurable and / or derivable electrical characteristics (e.g., waveform(s)).

[0075] At reference 635, the IED identifies new "normal" power event profiles (eg, typical power quality (PQ) profile(s)) for the electrical / power system using the captured waveforms. The event power profiles represent normal operating power events on the electrical / power system.

[0076] At reference 640, the IED determines whether there is a risk associated with the new "normal" power quality profile. If there is no risk, the IED updates the power quality profile digital repository with the new "normal" power quality profile. Otherwise, if there is a risk, at reference 650, the IED predicts a power event. Following reference 650, the IED may create an alarm report at reference 655, or create a maintenance task for the electrical / power system to reduce the risk of a power event occurring.

[0077] Process 600 or operations thereof may be initiated on an electrical / power system randomly or at predetermined time periods or under certain electrical characteristic conditions (e.g., higher or lower voltage, current, power, etc.) to sample a desired number of waveforms over time under different circumstances on the electrical / power system or a facility powered by the electrical / power system.

[0078] IV. Adjustable pre-event and post-event capture periods

[0079] According to an exemplary embodiment, the pre-event and post-event capture periods can be adjusted by analyzing and comparing pre-event and post-event measurement data (e.g., waveforms of voltage and / or current signals or other measurable and / or derivable electrical characteristics). To determine the pre-event capture period, the earliest time before the event detection (e.g., the earliest timestamp) is determined from the pre-event waveform of the voltage and / or current signal or other measurable and / or derivable electrical characteristics before a significant change occurs. To determine the post-event capture period, the longest time after the event endpoint is detected is determined from the post-event waveform of the voltage and / or current signal or other measurable and / or derivable electrical characteristics after a significant change occurs. Thus, the pre-event capture period can be adjusted to the period between the earliest time and the time when the event is detected as starting, and the post-event capture period can be adjusted to the period between the time when the event is detected as ending and the time when no significant change occurs thereafter. In some cases, these capture periods can be extended to the next half cycle or full cycle.

[0080] Significant changes may be determined based on threshold conditions (e.g., outside a certain range of a nominal or steady-state value of an electrical characteristic, such as outside ±10%, outside ±20%, etc.) Pre-event and post-event capture period analysis may be performed across multiple power phases and measured and / or derived electrical characteristics to determine sufficient pre-event and post-event capture periods to reduce or minimize the likelihood of missing important waveform data before and after a detected event period.

[0081] 8A, 8B, and 8C illustrate a flow diagram of an example process 800 by which waveform data is analyzed to adjust pre-event and / or post-event capture periods. By way of example, for purposes of explanation, the process 800 will be discussed with reference to a computer system (eg, an IED).

[0082] At reference 802, a voltage residual value is calculated by the IED. The voltage residual value may be the difference between actual data points of a measured voltage waveform and a reference curve.

[0083] At reference 804, a voltage reference change of the measured waveform is calculated by the IED. The variance of the pre-event residual voltage waveform may be a standard deviation, an interquartile range, or other determinable variance.

[0084] At reference 810, a timestamp of a voltage event start (e.g., exceeding an event threshold) is detected by an IED. The IED may be configured to detect the voltage threshold start of an event when a threshold condition is met (e.g., the voltage is within ±10% of the nominal voltage). At reference 812, an alternative timestamp of the start of the voltage event is calculated by the IED. For example, the IED detects a value in the residual curve that is greater than a reference variance prior to the start of the voltage event. At reference 814, the IED selects the earliest timestamp to define the start of the voltage event.

[0085] Similarly, at reference 820, a timestamp of a voltage threshold end of an event is detected by the IED. The IED may be configured to detect the voltage threshold end of an event when a threshold condition is met (e.g., voltage is less than ±10% of nominal voltage). At reference 822, alternative timestamps of the voltage end of the voltage event are calculated. For example, the IED identifies any value in the residual curve that is greater than a reference variance of the end of the voltage event. At reference 824, the IED selects the most recent timestamp to define the end of the voltage event.

[0086] Following reference 814 and reference 824, process 800 analyzes the current waveform(s) to determine the associated timestamps for the start / end of the current event, as further illustrated in the operations described in FIG8B. As shown in FIG8B, at reference 830, the IED calculates a current residual value (e.g., a residual value of the current). The residual value may reflect the difference between the actual data points of the current waveform and the reference curve. At reference 832, a current reference change of the measured waveform is calculated. The variance of the pre-event and / or post-event residual current waveform may be a standard deviation, an interquartile range, or other determinable variance.

[0087] At reference 840, the IED uses the voltage start of the event as the initial current start of the event. At reference 842, the IED calculates (multiple) alternative timestamps for the start of the current event. For example, the IED detects any value in the residual current curve that is greater than a reference variance before the threshold start of the event. At reference 844, the IED selects the earliest timestamp to define the current start of the event.

[0088] Similarly, at reference 850, the IED uses the voltage endpoint of the event as the initial current endpoint of the event. At reference 852, the IED calculates (multiple) alternative timestamps for the endpoint of the current event. For example, after the endpoint of the event, the IED detects any value in the residual curve that is greater than the reference variance. At reference 854, the IED selects the most recent (or later) timestamp to define the current endpoint of the event.

[0089] Following reference 844 and reference 854, process 800 selects the event best timestamp for the start / end point of the event, as shown in the operation of FIG8C. For example, as shown in FIG8C, at reference 860, the IED identifies the earliest timestamp by comparing the voltage start of the event and the current start of the event. At reference 862, the IED defines the identified earliest timestamp as the global event start. Similarly, at reference 870, the IED identifies the most recent timestamp by comparing the voltage end point of the event with the current end point of the event. At reference 872, the IED defines the most recent (or later) timestamp as the global event end point (e.g., "event end"). Once the global event start and end point are defined, at reference 880, the IED can calculate the pre-event period and the post-event period.

[0090] The example process 800 may assume that the residual voltage curve will also reflect any time glitches (this can be checked by calculation). There is a simple explanation for this assumption. For example, the sampling frequency may be fixed, which may be a setting of the IED (e.g., a meter or measuring device). Thus, if the solid curve of the measurement point is "shifted earlier" or "shifted later" (relative to the "reference sine wave"), the residual voltage value will increase or decrease because the residual voltage is measured from a normal point defined within the normal sine wave.

[0091] Although FIGS. 8A-8C describe an example where global event ends and starts of waveform capture periods are determined by evaluating current and voltage, other derivable electrical characteristics (eg, power) or combinations thereof may be analyzed to determine or adjust pre-event and post-event capture periods.

[0092] V. Phase Shift or Duration Analysis

[0093] The measurement data (e.g., waveform(s)) may be analyzed to determine phase shifts or changes, which may provide additional information related to the detected event. To perform such analysis, the waveform(s) may be analyzed by evaluating the zero crossings to determine the duration of each half cycle of the waveform, thereby adjusting the pre-event or post-event capture period. Based on the duration information, significant or relevant phase shifts may be identified that may reflect some change in the electrical / power system and, therefore, should be evaluated or analyzed in more detail. It may also be determined whether the shift in the zero crossing from pre-event to post-event reflects a change in the power supply.

[0094] 9A and 9B illustrate a flow diagram of an example process 900 by which pre-event and post-event periods (eg, 880 of FIG. 8C ) may be calculated. By way of example, for purposes of explanation, the process 900 will be described with reference to an IED.

[0095] At reference 910, the IED uses the global event start to identify the measurement point before the timestamp. At reference 912, the IED calculates the zero crossings (eg, using linear extrapolation or other mathematical methods). At reference 914, the IED calculates the half-cycle duration before each event (pre-event).

[0096] At reference 920, the IED uses the global event end to identify the measurement point after the timestamp. At reference 922, the IED calculates the zero crossing (eg, using linear extrapolation or other mathematical methods). At reference 924, the IED calculates the half-cycle duration after each event.

[0097] At reference 930, if necessary, the IED may perform extrapolation after references 914 and 924. Process 900 thereafter proceeds to operations on FIG. 9B. For example, as shown in FIG. 9B, at reference 940, the IED counts the pre-event half cycles and identifies any incomplete half cycles. At reference 942, the IED determines whether the count of the pre-event half cycles is sufficient (e.g., greater than a minimum quality indicator, which, for example, begins at reference 944 as two and a half (2 1 / 2) cycles). If so, process 900 proceeds to reference 980, where the IED may use the pre-event and post-event periods to extract dimensions, infer meaning, and infer recommendations or actions (e.g., after the pre-event and post-event half cycle counts are sufficient or after extrapolation of missing values). These operations may be performed, for example, according to predefined rules.

[0098] If not sufficient at reference 942, the IED may use the timestamps of the zero crossings of other phases and apply them at reference 944 to construct a new half cycle for that phase. At reference 946, the IED determines whether the new counts for the half cycle before the event are sufficient. If the new counts are sufficient, process 900 proceeds to reference 980. Otherwise, if the counts are not sufficient at reference 946, the IED identifies the best split of the half cycle at reference 948. At reference 950, the IED extrapolates the missing values ​​from the reference curve to create the missing complete half cycle and proceeds to operation in reference 980. A warning may be provided that the analysis is using extrapolated data.

[0099] The above operations can also be performed on the side after the event. For example, turning to reference 960, the IED counts the half-cycle after the event and identifies any incomplete half-cycle. At reference 962, the IED determines whether the count of the half-cycle after the event is sufficient. If the count is sufficient, the process 900 advances to reference 980, where the IED can use the pre-event and post-event periods to extract dimensions, infer meanings, and infer suggestions or actions (e.g., after the pre-event and post-event half-cycle counts are sufficient or after the extrapolation of missing values). For example, these operations can be performed according to predefined rules.

[0100] If the count is insufficient at reference 962, then at reference 964, the IED may use the timestamps of the zero crossings of the other phases and apply them to construct a new half cycle for that phase. At reference 966, the IED determines whether the new count for the half cycle after the event is sufficient. If it is sufficient, the process 900 proceeds to reference 980. Otherwise, if the count is insufficient at reference 966, then at reference 968, the IED identifies the best split of the half cycle. At reference 970, the IED extrapolates the missing values ​​to create the missing complete half cycle with respect to the reference curve, and then proceeds to the operation in reference 980. As previously described, a warning may be provided that the analysis is using extrapolated data.

[0101] At reference 980, once sufficient pre-event and post-event periods have been captured for the waveform(s), the IED may perform various analyses and actions locally or in conjunction with remote devices or systems. For example, the IED may extract dimensions associated with the event, detect excursions in zero crossings, detect significant changes in half-cycle durations, and perform other analyses and actions described herein.

[0102] VI. Computer System

[0103] As shown in FIG. 10 , a computer system 1000 (e.g., an IED) may include, for example, one or more sensors 1010, a memory 1020, (multiple) processors 1030, a clock 1040, an output device 1050, an input device 1060, a communication device 1070, and a bus system 1080 between IED components. In various embodiments, the sensor 1010 may be configured to sense a voltage and / or current signal or other measurable and / or derivable electrical characteristic from a power line on an electrical / power system. The sensor 1010 may include signal processing and conditioning circuitry to measure an energy-related signal (e.g., a voltage or current signal waveform) that represents a voltage and / or current signal or other measurable and / or derivable electrical characteristic on an electrical / power system. The clock 1040 may be used to time stamp measurement data, event data, event profile data, or other types of data measured, calculated, captured, stored, or generated by the IED.

[0104] The memory 1020 may store computer executable code, programs, software, or instructions that, when executed by a processor, may control operations such as those described herein. The memory 1020 may also store other data used by the computer system 1000 or its components to perform the operations described herein. The other data may include, but is not limited to, a digital repository of typical power events (e.g., power quality events, typical power events, atypical power events, or other related events), a digital repository of typical non-event profiles, alarm events, thresholds, (multiple) states, and / or measurement data (e.g., captured waveforms, parameters, and thresholds, and other data discussed herein). The memory 1020 may also include a temporary storage device (e.g., (multiple) buffers) to enable discrete recording of measured and / or derived data, so that the desired amount of measurement data (e.g., waveforms) may be measured, derived, captured, and / or stored.

[0105] Input device(s) 1060 and output device(s) 1050 may include, for example, a keyboard or keypad, a mouse, a trackball, a microphone, a touch screen, a printing device, a display screen, speakers, etc. For example, output device(s) 1050 may render information for external presentation (e.g., a display device), and input devices may accept information from external sources (e.g., users and other systems).

[0106] The processor(s) 1030, interacting with other components of the computer system, is configured to control or implement various operations described herein. These operations may include monitoring, measuring and / or inferring electrical parameters of the gas / power system, waveform capture (WFC), event analysis, event profile creation, and other IED operations (e.g., measurement, calculation, alarm, reporting, control, etc.). Energy-related signals (e.g., voltage or current waveforms) may be sampled at a desired rate to obtain sufficient resolution (e.g., 32 samples / cycle or 2048 samples / cycle) of the data for calculation or analysis.

[0107] Example components of a computer system (e.g., an IED or a network node) are described above. The IED or network node may be a power meter, a circuit breaker, and / or other computer or intelligent system / device that may report event data to other computer systems and devices (e.g., a control node or a central monitoring system on a network) for further analysis and action.

[0108] It should also be understood that the exemplary embodiments disclosed and taught herein are susceptible to numerous and various modifications and alternative forms. Therefore, the use of singular terms, such as but not limited to "one", etc., is not intended to limit the number of items. In addition, the naming conventions of various components, functions, features, thresholds, parameters and / or elements used herein are provided as examples and may be given different names or labels. The use of the term "or" is not limited to an exclusive "or" and may also mean "and / or". The use of the slash symbol " / " may mean "or" or "and / or".

[0109] It should be understood that the development of practical, real business applications in conjunction with various aspects of the disclosed embodiments will require many implementation-specific decisions to achieve the developer's goals for the business embodiments. Such implementation-specific decisions may include, and may not be limited to, compliance with system-related, business-related, government-related, and other constraints, which may vary depending on the specific implementation, location, and time. While the developer's efforts may be complex and time-consuming in an absolute sense, such efforts are still routine tasks for those skilled in the art who benefit from this disclosure.

[0110] Using the description provided herein, the example embodiments may be implemented as a machine, process, or article of manufacture by using standard programming and / or engineering techniques to produce programming software, firmware, hardware, or any combination thereof.

[0111] Any (multiple) final programs with computer-readable program code may be contained on one or more computer-usable media, such as a resident memory device, a smart card or other removable memory device or a transmission device, thereby manufacturing a computer program product or article of manufacture according to an embodiment. Therefore, the terms "article of manufacture" and "computer program product" as used herein are intended to cover a computer program that exists permanently or temporarily on any computer-usable medium or any transmission medium that transmits such a program.

[0112] The processor(s) or controller(s) described herein may be a processing system that may include one or more processors, such as a CPU, GPU, controller, FPGA (field programmable gate array), ASIC (application specific integrated circuit), or other dedicated circuit or other processing unit, that controls the operation of the device or system described herein. Memory / storage devices may include, but are not limited to, disks, solid-state drives, optical disks, removable storage devices such as smart cards, SIMs, WIMs, semiconductor memories (such as RAM, ROM, PROMS, etc.). Transmission media or networks include, but are not limited to, transmission via wireless communications (e.g., Radio Frequency (RF) communications, Bluetooth®, Wi-Fi, Li-Fi, etc.). Internet, intranet, telephone / modem-based network communications, hardwired / cabled communication networks, satellite communications, and other fixed or mobile network systems / communication links.

[0113] In addition, capture, analysis, profiling, reporting, and other operations can be performed at a network node, such as a power meter or other equipment associated with or on a distribution network, or across multiple network nodes in a distributed and hierarchical manner to monitor and analyze power quality throughout an electrical / power system (e.g., utilities and facilities), and implement reporting and actions accordingly to improve or maintain power quality.

[0114] While particular embodiments and applications of the present disclosure have been illustrated and described, it will be understood that the disclosure is not limited to the precise construction and composition disclosed herein and that various modifications, changes and variations will be apparent from the foregoing description without departing from the invention as defined in the appended claims.

Claims

1. A method for analyzing an electrical energy event in an electrical power system using at least one processor and a sensor, the method comprising: monitoring at least one of a voltage and a current signal in the electrical power system; identifying at least one electrical energy event in the electrical power system based on at least one of the monitored voltage and current signals; responsive to identifying the at least one electrical energy event, capturing a waveform of at least one of the monitored voltage and current signals from a first time period prior to the onset of the at least one identified electrical energy event to a second time period after the endpoint of the at least one identified electrical energy event; determining energy-related information based on pre-event measurements using the captured waveform, the energy-related information determined based on the pre-event measurements including at least one of an energy-related parameter, a signal, an indicator, a state, and other information; determining energy-related information based on post-event measurements using the captured waveforms, the energy-related information determined based on the post-event measurements including at least one of an energy-related parameter, a signal, an indicator, a state, and other information; identifying and / or deriving and / or calculating additional information associated with the at least one identified electrical energy event by comparing (a) energy-related information determined from pre-event measurements and (b) energy-related information determined from post-event measurements; as well as performing at least one action affecting at least one component in the electrical power system, providing additional actionable information to an event report, or providing an extracted signal to an automated event analysis system, The method further comprises: determining at least one cause of the at least one identified electrical energy event based on the additional information; or An impact of the at least one identified electrical energy event on equipment in the electrical power system is determined.

2. The method according to claim 1, wherein: The at least one identified power event comprises a power quality event.

3. The method according to claim 1, wherein: The additional information includes distinguishing additional information, and the distinguishing additional information is used to describe which type of load in the electrical power system is disconnected or de-energized, or added or energized in response to the electric energy event.

4. The method according to claim 1, wherein: Waveform capture is performed by at least one intelligent electronic device (IED) in the electrical power system, the intelligent electronic device being coupled to electrical power system equipment.

5. The method according to claim 1, wherein: The at least one component comprises equipment in the electrical power system.

6. The method according to claim 1, wherein: The first time period or the second time period is adjustable according to electrical or power conditions in the electrical power system.

7. The method according to claim 1, wherein: The at least one identified power event includes at least one power quality event, and the first time period or the second time period is variable according to a duration of the at least one power quality event.

8. The method according to claim 1, wherein: Energy-related information determined based on pre-event measurements and / or energy-related information determined based on post-event measurements include at least one of alternating current (AC) and / or direct current (DC) voltage signals, AC and / or DC current signals, power, distortion, DC offset, noise, discrete phase data, frequency, phase angle, state or occurrence of load loss, percentage of load loss, power factor change, change in steady-state voltage / current shape, and / or other measured and / or derived information, wherein the state or occurrence of load loss can reflect that something was added to or removed from the electrical power system during the at least one identified electrical energy event.

9. The method according to claim 1, wherein: Energy-related information determined based on pre-event measurement values ​​and / or energy-related information determined based on post-event measurement values ​​indicates whether a load is added to or removed from the electrical power system during at least one identified electrical energy event, the addition of the load indicating power-on of the load, and the removal of the load indicating power-off of the load.

10. The method according to claim 1, wherein: The at least one identified electrical energy event is detected and classified by monitoring, identifying, capturing and analyzing measured data and / or derived data associated with at least one of the monitored voltage and current signals.

11. The method according to claim 1, wherein: The captured waveforms are analyzed to identify relevant representative parameters, elements and / or statistical / analytical dimensions, such as amplitude of electrical characteristics, harmonic distortion, power factor, duration of identified electrical energy events, event severity, origin of interference sources, or other event characteristics.

12. The method according to claim 1, wherein: The at least one action is performed by a power meter, a protection device, a load, a process, a control device, or other system / device associated with the electrical power system.

13. The method according to claim 1, wherein: The additional information comprises a phase shift of the energy dependent signal, the phase shift satisfying at least one phase shift criterion.

14. The method according to claim 1, wherein: The other information includes the location of certain components in the electrical power system.

15. The method according to claim 1, further comprising: When the captured waveform represents an unknown event profile of the electrical power system, creating a new event profile based on the captured waveform; as well as The digital repository stored in memory is updated with the new event profile.

16. A system for analyzing electrical energy events in an electrical power system, the system comprising: Memory; one or more sensors configured to sense at least one of a voltage and a current signal in the electrical power system; as well as One or more processors configured to: monitoring at least one of a voltage and a current signal using the one or more sensors; identifying at least one electrical energy event in the electrical power system based on at least one of the monitored voltage and current signals; responsive to identifying the at least one electrical energy event, capturing a waveform of at least one of the monitored voltage and current signals from a first time period prior to the start of the identified electrical energy event to a second time period after the end of the identified electrical energy event; determining energy-related information based on pre-event measurements using the captured waveform, the energy-related information determined based on the pre-event measurements including at least one of an energy-related parameter, a signal, an indicator, a state, and other information; determining energy-related information based on post-event measurements using the captured waveforms, the energy-related information determined based on the post-event measurements including at least one of an energy-related parameter, a signal, an indicator, a state, and other information; identifying and / or deriving and / or calculating additional information associated with at least one identified electrical energy event by comparing (a) energy-related information determined from pre-event measurements and (b) energy-related information determined from post-event measurements; as well as performing at least one action affecting at least one component in the electrical power system, providing additional actionable information to an event report, or providing an extracted signal to an automated event analysis system, wherein the one or more processors are further configured to: determining at least one cause of the at least one identified electrical energy event based on the additional information; or An impact of the at least one identified electrical energy event on equipment in the electrical power system is determined.

17. The system of claim 16, wherein: The at least one identified power event comprises a power quality event.

18. A tangible computer medium storing computer executable code, the computer executable code, when executed by a processor, being configured to implement a method of analyzing an electrical energy event in an electrical power system, the method comprising: monitoring at least one of a voltage and a current signal in the electrical power system; identifying at least one electrical energy event in the electrical power system based on at least one of the monitored voltage and current signals; In response to identifying the power event, capturing a waveform of at least one of the monitored voltage and current signals from a first time period before the start of the identified power event to a second time period after the end of the identified power event; determining energy-related information based on pre-event measurements using the captured waveform, the energy-related information determined based on the pre-event measurements including at least one of an energy-related parameter, a signal, an indicator, a state, and other information; determining energy-related information based on post-event measurements using the captured waveforms, the energy-related information determined based on the post-event measurements including at least one of an energy-related parameter, a signal, an indicator, a state, and other information; identifying and / or deriving and / or calculating additional information associated with at least one identified electrical energy event by comparing (a) energy-related information determined from pre-event measurements and (b) energy-related information determined from post-event measurements; as well as performing at least one action affecting at least one component in the electrical power system, providing additional actionable information to an event report, or providing an extracted signal to an automated event analysis system, The method further comprises: determining at least one cause of the at least one identified electrical energy event based on the additional information; or An impact of the at least one identified electrical energy event on equipment in the electrical power system is determined.

Images