method performed by a data processing apparatus, computer readable storage system and media for grid

专利摘要:
GRID EVENT DETECTION Data communication over a network of power lines, methods, systems, and apparatus, including computer programs encoded in a computational storage medium, to detect grid events. In one aspect, a method includes receiving signal characteristic data that specify signal characteristic values for signals that are received by each of a plurality of communications channels of a powerline communications network. A determination is made that the signal characteristic values that are received by at least one of the communications channels are outside a baseline signal value range. An endpoint that communicates over at least one communications channel is identified, and a determination is made that a set of signal characteristic values for the identified endpoint matches one of a plurality of grid event signatures for the identified endpoint. Data is provided that identifies the endpoint and a particular grid event that is represented by the matched grid event signature.
公开号:BR112013025139B1
申请号:R112013025139-5
申请日:2012-03-09
公开日:2021-05-04
发明作者:Stanley E. Mchann
申请人:Landis+Gyr Technologies, Llc；
IPC主号:

专利说明:

RELATED PATENT DOCUMENT
[001] This patent document claims priority to U.S. Patent Application Serial Number 13/075,646 filed March 30, 2011, the contents of which are incorporated herein in their entirety by reference. FUNDAMENTALS
[002] This descriptive report refers to the detection of grid events.
[003] Service providers use distributed networks to provide services to consumers in large geographic areas. For example, communications companies use a distributed communications network to provide communications services to consumers. Similarly, energy companies use a network of power lines and meters to supply energy to consumers across a geographic region.
[004] These service providers depend on the proper operation of their respective networks to distribute the services to consumers, because operational problems in the network can result in the loss of revenue for the service provider. For example, the service provider may lose revenue based on an inability to provide a service during a network outage. Therefore, when a network outage or other network event that disrupts service occurs, it is in the service provider's interest to identify the cause of the problem and fix the problem as soon as possible. In many distributed networks, service providers first receive an indication there is a problem with the network based on feedback from consumers. For example, consumers can call their service provider to report a network outage. Based on the information received from the consumers, the service provider can take action to remedy the problem with the network. For example, a service provider can access endpoints on the network to retrieve additional information regarding the status of the network and/or dispatch workers to try to identify the problem.
[005] Although a service provider can remedy network outages and other network problems by accessing endpoints on the network network and/or dispatching workers, the time and resources needed to identify the cause of the outage or problem can result in a significant loss of revenue for the service provider. So, if a service provider can reduce the time it takes to identify if there is a problem in a network, or even prevent the problem before it occurs, the service provider can reduce lost revenue due to network outages and increase revenue. satisfaction of consumers. SUMMARY
[006] In general, an innovative aspect of the subject described in this descriptive report can be incorporated in methods that include the actions of receiving, through a data processing apparatus, signal characteristic data that specify the signal characteristic values for signals that are received by each of the plurality of communications channels of a power line communications network; determining, by the data processing apparatus, that the signal characteristic values for the signals that are received by at least one of the communications channels are outside a baseline signal value range; identify an endpoint that communicates over at least one communications channel; determining that a set of signal characteristic values correspond to a plurality of grid event signatures for the identified endpoint, each of the grid event signatures being indicative of a particular grid event; and providing data identifying the endpoint and the particular grid event for the grid event signature that is matched by the set of monitored signal characteristics. Other modalities of this aspect include systems, apparatus, and corresponding computer programs configured to perform the actions of the methods, encoded in computational storage devices.
[007] These and other modalities may optionally include one or more of the following features. Determining that the set of signal characteristic values matches one of a plurality of grid event signatures may include determining that the set of signal characteristic values matches a grid event signature for one of a bank failure ca-pacitor, a power failure, or a capacitor bank activation. Identifying an endpoint that communicates over the communications channel may include identifying an endpoint identifier for the endpoint that communicates over the communications channel, the endpoint identifier being identified from a index of endpoint identifiers for endpoints and communications channels through which each of the endpoints communicate.
[008] Methods may further include one or more of the actions of accessing map data that specify geographic locations of endpoints; determining a geographic location of the identified endpoint based on map data; identifying network elements that are within a threshold distance from the geographic location of the identified endpoint; and identifying a particular network element in the set of network elements that is contributing to the grid event, the identification being based on at least the location of the identified endpoint, the location of the particular network element, or in the particular grid event.
[009] The methods may further include the action of determining that one or more additional network elements in the set of network elements are not being affected by the particular grid event. Determining which one or more additional network elements are being affected by the particular grid event may include for each one or more additional network elements: comparing a set of signal characteristic values for the network element to the grid event signature for the particular grid event; and determining that the set of signal characteristic values corresponds to the grid event signature.
[010] The methods may further include the action of providing data that cause the presentation of a map interface that visually identifies a geographic location of the network element that is contributing to the particular grid event and a geographic location of one or plus additional network elements that are also being affected by the particular grid event.
[011] The methods may further include the action of updating the map interface in response to the determination that a new network element has been determined to be one or more additional network elements, with the map interface being updated to identify visually the geographic location of the new network element.
[012] Methods may further include one or more of the actions of receiving status data from a network element that specifies a reported state of the network element; determining, based on the received signal characteristic values, that the status data coming from the network element is invalid; and providing data that specifies a current state of the network element.
[013] The particular modalities of the subject described in this descriptive report may be implemented in order to realize one or more of the following advantages. A data processing apparatus can be configured to determine that a grid event exists and a location of a network element causing the grid event. The time required to determine that a grid event has occurred and/or the source of the grid event can be reduced by using characteristics of continuously monitored communications signals to determine the existence of a grid event. The location of the network element causing the grid event can be determined using map data so that service personnel can be dispatched.
[014] Details of one or more modalities of the subject described in this descriptive report are presented in the attached drawings and in the description below. Other features, aspects, and advantages of the subject matter will become apparent from the description, drawings, and claims. BRIEF DESCRIPTION OF THE DRAWINGS
[015] Figure 1 is a block diagram of an exemplary network environment in which the endpoints transmit data.
[016] Figure 2A is a graph that illustrates an exemplary signal that can be received by a communications channel.
[017] Figure 2B is a graph of another exemplary signal that can be received by a communications channel.
[018] Figure 3 is a flowchart of an exemplary process to detect grid events.
[019] Figure 4 is a flowchart of an exemplary process to identify endpoints that are affected by a grid event.
[020] Figure 5 is a block diagram of an exemplary system that can be used to facilitate the detection of the grid event.
[021] Numerical references and similar designations in the various drawings indicate similar elements. DETAILED DESCRIPTION
[022] Figure 1 is a block diagram of an exemplary network environment 100 in which the endpoints transmit data. The network environment 100 includes a service network 101 in which a plurality of endpoints 102a-102f (collectively referred to as endpoints 102) are coupled (e.g., communicatively coupled) to a processing unit. substation 104. Endpoints 102 are network elements of network 101 and can be any device capable of transmitting data in the environment of network 100. For example, endpoints 102 can be meters or other elements of a utility network, computing devices, television decoder terminals, or telephones that transmit data on the service network. The following description refers to endpoints 102 as power meters in a power distribution network. However, the following description is applicable to other types of endpoints 102 in utility networks or other networks. For example, the following description is applicable to gas meters and hydrometers that are respectively installed in gas and water distribution networks.
[023] Endpoints 102 can be implemented to monitor and report various operational characteristics of the service network 101. For example, in a power distribution network, endpoints 102 may include meters that can monitor the characteristics related to the use of energy in the network. Exemplary characteristics related to grid power usage include average or total power consumption, power spikes, power outages, and load changes, among other characteristics. In gas and water distribution networks, meters can measure similar characteristics that are related to gas and water usage (eg total flow and pressure).
[024] The endpoints 102 and substation 104 communicate with each other by communications channels. Communications channels are portions of a spectrum over which data is transmitted. The central frequency and bandwidth of each communications channel may depend on the communications system in which they are implemented. In some implementations, communication channels for utility meters (eg, energy, gas and/or water meters) can be implemented in power line communication networks (PLC) that dynamically allocate available bandwidth accordingly with an orthogonal frequency division multiple access (OFDMA) spectrum allocation technique or another channel allocation technique. (for example, Time Division Multiple Access, Code Division Multiple Access, and Frequency Division Multiple Access techniques).
[025] When using OFDMA, each endpoint 102 is assigned a subset of available data subcarriers so that multiple endpoints can simultaneously transmit data over the service network 101, even when endpoints 102 have different requirements of bandwidth. For example, when a modulation technique being used to transmit data from one endpoint requires more bandwidth than required by another modulation technique being used to transmit data from a second endpoint, the first endpoint can allocate more subcarriers (that is, bandwidth) than the second endpoint. In some implementations, a channel is a set of two or more contiguous subcarriers, while in some implementations, a channel is a set of one or more subcarriers. OFDMA is provided as an exemplary spectrum allocation technique, but other allocation techniques may also be used (for example, Time Division Multiple Access, Code Division Multiple Access, and Multiple Access techniques per Frequency Division).
[026] The OFDMA subcarriers and/or channels can be allocated in an order that is based on the characteristics of the subcarrier (or channel). For example, subcarriers (or channels) can be sorted according to their respective noise floors (eg sorted in ascending order of noise floor). In these implementations, the quietest subcarriers (that is, the subcarriers having the lowest noise floor) are allocated before the subcarriers having the highest noise floors. The noise floor of a subcarrier and/or a channel can be, for example, an average amplitude of noise signals that are measured across the spectrum of the subcarrier and/or the channel. The average noise amplitude can be the method noise in the channel for a specific period, such as a previous hour, day, or week. The noise floor can also be specified as a maximum noise floor, a median noise floor, or other statistical measure of noise across the subcarrier and/or channel spectrum.
[027] When endpoints 102 are implemented, for example, as energy meters in a power distribution network, the data transmitted over the channels by the energy meters can represent measurements of total energy consumption, consumption of power over a specified period of time, peak power consumption, instantaneous voltage, peak voltage, minimum voltage, and other measurements related to power consumption and power management (eg, load information). Each of the power meters can also transmit status data that specifies a power meter's status (for example, operating in a normal operating mode or an emergency power mode). Data representing measurements related to energy consumption and/or status of the energy meter, as well as other data that is transmitted by the energy meter (or other endpoints) is referred to as data representing meter information.
[028] In some implementations, data representing meter information (eg, data representing power consumption measurements and/or status data) is continuously or intermittently transmitted over a specific unit interval. A unit interval is a period of time during which a particular symbol (that is, one or more bits) is transmitted. A unit interval for each symbol transmitted by an energy meter may be less than or equal to the time interval (i.e., 1/refresh rate) at which endpoint 102 is required to provide the updated meter information. For example, it is assumed that a particular meter is required to provide meter information updated every 20 minutes (ie, the meter-specific update rate). In this example, a meter can transmit a symbol that represents a first set of updated meter information for twenty minutes, and then transmit another symbol that represents a next set of updated meter information for a subsequent period of twenty minutes.
[029] The update rate and/or unit interval for a meter can be specified by a network administrator based, for example, on the types and amounts of updated meter information being received from the meter, preferences of a consumer (eg a power company) to which the data is being supplied, and/or channel characteristics of the channel over which the data is being transmitted.
[030] The endpoints 102 transmit the data representing the meter information over the communications channels to a substation processing unit 104. The substation processing unit (SPU) 104 is a data processing apparatus which receives communications from endpoints 102 and uses the data included in the communications to manage the service network 101 and/or transmits the data from the communications to another processing apparatus. For example, the SPU 104 may include a receiver that receives symbols 106 from endpoints 102 and records data from the symbols. The SPU 104 can also take an action based on the data that is included in the symbols 106 that are received from the endpoints 102, or transmit the symbols 106 to a network management apparatus 108 that manages the service network 101. The SPU 104 can transmit the individual symbols 106 or generate a consolidated packet that includes multiple symbol data 106 received from the endpoints 102.
[031] Other network elements may also communicate with the SPU 104. For example, a capacitor bank (“CB”) 112 and a switch 114 may include a communications apparatus that transmits status information to the SPU 104. statuses transmitted by capacitor bank 112 may include, for example, data that specifies whether capacitor bank 112 is coupled to the network. For example, SPU 104 can transmit activation instructions (instructions that cause the capacitor to be electrically coupled to network 101) to capacitor bank 112. In response to receipt of activation instructions, capacitor bank 112 can execute instructions that cause that the capacitor bank 112 is activated, so that the capacitor bank is electrically coupled to the network 101. In turn, the capacitor bank 112 may transmit confirmation data indicating that the capacitor bank has been activated. Similar data transmissions can occur when the capacitor bank needs to be deactivated.
[032] Similar data communications may also occur between the SPU 104 and other network elements. For example, the switching instructions may be transmitted by the SPU 104 to the network switch 114 which may be selectively opened or closed by instructions which are transmitted to the switch 114. Successively, the switch may process the instructions, and transmit the acknowledgment data which indicate that the switch has processed the instructions and/or that the switch has transitioned into a particular configuration state with the instructions. The configuration state that is reported by a network element is referred to as a reported state of the network element. Although receipt of acknowledgment data specifying the reported state of the network elements is indicative of the network element being configured such that the current state of the element matches the reported state, it is possible that the acknowledgment data (ie, the data specifying the reported state) does not accurately reflect the current state of the network element.
[033] For example, hardware or software errors in the network element can cause the acknowledgment data to incorrectly specify the configuration (ie, the current state) of the network element. In a particular example, if switch 114 has a hardware failure that prevents the switch from closing, it is possible that switch 114 may have a current state of open while transmitting confirmation data that specifies a reported state of closed. Similar errors can result in acknowledgment data being received from capacitor bank 112 incorrectly indicating a reported on (or off) state for capacitor bank 112 when the capacitor bank has a current off (or on) state.
[034] When network elements malfunction or remain in a state (for example, open or closed, enabled or disabled, or coupled or uncoupled from the network) that is different from the reported state, it can be difficult to transmit with communications over network 101 succeeds. For example, switch 114 is assumed to remain open after SPU 104 transmits instructions for switch 114 to close. It is further assumed that switch 114 that was closed in response to the determination that a power line 116 was cut or that another network element that is connected to power line 116 was malfunctioning. In this example, transmissions from endpoints 102d-102f that were being received by SPU 104 over power line 116 may not be received by SPU 104 if the switch is not currently closed. However, it can be difficult to determine that the switch was not currently closed without dispatching a service team to the location of the switch 114, particularly if acknowledgment data from the switch indicates that the switch was closed.
[035] Environment 100 includes a network management apparatus 108, which consists of a data processing apparatus that facilitates the detection of the grid event and provides information and/or instructions that can be used to address the grid event ( for example, terminate the grid event, adjust network element settings, or otherwise take action in response to detection of the grid event). In some implementations, the network management apparatus 108 receives signal characteristic data from the SPU 104 and/or directly from the endpoints 102. The signal characteristic data specifies a set of signal characteristic values of signals that are received by each communications channel (“channel”) of the network 101 network.
[036] For example, the set of signal characteristic values can specify one or more of a range of communications signals that are received by a channel, a noise floor of the channel by which the signals are being received, and/or a measurement between signal and noise (eg Eb/No) for the signals being received by the channel. Signal characteristic values can also include values such as peak amplitude, minimum amplitude, maximum amplitude, duty cycle, and/or frequency measurements.
[037] The set of signal characteristic values may include instantaneous signal characteristic measurements and/or signal characteristic values that represent the measurements of signal characteristics over time. For example, signal characteristic values can specify an instantaneous measurement of signal amplitude and/or a periodic mean amplitude (or other central tendency measurement for amplitude).
[038] The network management apparatus 108 can determine, for each channel, whether the signal characteristic values for the channel are outside a baseline signal value range for the channel. The baseline signal value range is a range of signal values that have been specified (for example, by a network administrator and/or based on historical data analysis) as valid values for the signal value characteristics. . For example, as described in more detail with reference to Figure 2A, the baseline signal value range can specify a set of maximum acceptable amplitudes of and a set of minimum acceptable amplitudes for the signals that are received by the channel. The baseline signal value range may remain constant over time or may vary over time, and may be based on a statistical analysis of signals that were previously received by the communications channels.
[039] When the signal characteristic values remain within the baseline signal value range, the network management apparatus 108 can continue to monitor the signal characteristic values. When the network management apparatus 108 determines that the signal characteristic values are outside the baseline signal value range, the network management apparatus 108 can determine whether the signal characteristic values that have been acquired, for example, during a specified period (e.g., one or more previous unit intervals) indicate that a particular grid event has occurred in the network 101. For example, as described with reference to Figure 3, the network management apparatus 108 can determine whether the signal characteristic values that were received during the specified period correspond to a grid event signature (that is, a set of signal characteristic values that are indicative of the grid event) that is stored in a grid event data store. grid. If it is determined that a match exists, the network management apparatus 108 can determine that the grid event is occurring (or has occurred), and provides data (e.g., to a user device 118 or the SPU 104).
[040] In some implementations, grid event signatures are stored in a 120 grid event data store. The grid event store can include a list of grid events and grid event signatures corresponding (i.e., signal characteristic values that are indicative of the grid event) that are associated (ie, indexed according to or stored with reference to) a grid event. The list of grid events can include, for example, a transformer failure, a reclosure failure, a capacitor bank trip, a capacitor bank trip, a capacitor bank failure, a closure of switch, a power outage, and/or other grid events. The grid event signatures that are associated with each of the grid events can be specified on a per-channel basis so that the signal characteristic values that define a particular grid event can differ on a per-channel basis. Therefore, a particular grid event can be identified on each particular channel based on a grid event signature that has been specified for that particular channel.
[041] The grid event signatures for each channel can be based, for example, on an analysis of signal characteristic values that were received by the channel during previous occurrences of grid events. For example, machine learning techniques can be used to select, for each channel, a set of signal characteristic values that are indicative of the occurrence of a grid event based on the signal characteristic values that were received when it was known that the grid event was taking place.
[042] In some implementations, the network management apparatus 108 can also determine the locations of endpoints 102 that are being affected by the grid event. For example, as described in more detail with reference to Figure 4, the network management apparatus 108 can access map data that is stored in a map data store 122 to determine the location of an endpoint being affected by the grid event. The map data store 122 may store a set of endpoint identifiers (e.g., EP1-EPi) that uniquely identify each of the endpoint 102 and geographic location information, such as a pair of Latins. - tude/longitude (eg Lat1:Lon1-Lati:Loni), an address, or a distance from a geographic reference location, for each of the endpoints that are identified by the endpoint identifiers .
[043] When the network management apparatus 108 determines that a particular endpoint (eg 102e) is being affected by the grid event, the network apparatus 108 can access the map data store 122 to determine the location geographic location of the particular endpoint. For example, the network management apparatus 108 may use the endpoint identifier that identifies the particular endpoint to retrieve geographic location information for the endpoint. As described below with reference to Figure 4, the network management apparatus 108 can use the geographic location of the particular endpoint to identify additional endpoints that are likely to be affected by the grid event, and determine whether each of the endpoints additional endpoints is being affected based on the signal characteristic values for the additional endpoint and the channel-specific (or endpoint-specific) grid event signature (ie, the endpoint-specific event signature of grid for the channel over which the endpoint communicates) for the particular grid event.
[044] Figure 2A is a graph 200 illustrating an exemplary signal 202 that can be received by a communications channel. For discussion purposes, graph 200 presents a signal 202 that was received by a single channel from time T0 to time T4 (for example, one or more unit intervals), and the following discussion refers to an event signature. which is defined for a single channel based on signal 202. However, as described above, signals can be received by each channel of a communications network, and event signatures can be defined on a per-channel (or per-point) basis. where each channel can have a different grid event subscription for a particular grid event. Therefore, multiple signals can be received by multiple channels, and multiple grid event signatures can exist for each particular grid event. Grid events are described below as affecting the signals that are received by communications channels. When a grid event affects a signal, the grid event is also considered to have affected the endpoint that transmitted the signal and/or the channel on which the signal is received.
[045] As described above, one can use an analysis of signal 202 (and other signals that were previously received for the channel) to determine a baseline signal value range for the signals that are received for the channel. For example, the historical average of signal 202 during reference periods (that is, when no grid event is occurring) is assumed to be represented by line 204. Furthermore, it is assumed that the average maximum signal level ( or another statistical measurement of amplitude that specifies a measurement of maximum signal value) for signal 202 during the reference periods is represented by line 206, and the average minimum signal level (or other statistical measurement of amplitude that specifies the minimum signal level value) for signal 202 during reference periods is represented by line 208. In this example, the baseline signal value range for signal 202 may be an amplitude range from the amplitude at line 208 to the amplitude at line 206. Thus, although signal 202 has an amplitude that is between lines 208 and 206, signal 202 can be determined to be within the baseline signal value range. However, since signal 202 has an amplitude that exceeds the amplitude at line 206, or is below the amplitude at line 208, the signal is considered to be outside the baseline signal value range.
[046] As described above, when signal 202 is determined to be out of the baseline signal value range, a determination can be made whether the signal characteristic values for signal 202 correspond to an event signature of grid. Grid event signatures for a channel can be defined based on characteristic signal values for signals that were received by the channel during and/or within a threshold time of the occurrence of a grid event. For example, the periods from time T0 to time T1 and from time T3 to T4 are supposed to represent periods in which no grid events occurred. Furthermore, the time period T2 to T3 is assumed to be a period during which a capacitor bank was known to be activated.
[047] As illustrated in graph 200, the amplitude of signal 202 has dropped (in relation to the amplitude during the period T0 to T1) when the capacitor bank is activated. However, the amplitude is still non-zero (eg, relative to the noise floor) and/or above a threshold amplitude value (eg, as represented by line 210). Therefore, although the signal amplitude has dropped, it is unlikely that the endpoint is being affected by a power outage since the amplitude is not substantially equal to zero (for example, in relation to the noise floor). Correspondingly, it could be that another grid event (for example, in addition to a power outage) is affecting the signals being received from the endpoint.
[048] Analysis of signals received by the channel during periods when a capacitor bank was active can reveal that the signals remained within an amplitude range that is between lines 210 and 212, which can define the grid event signature for activation of a capacitor bank. Therefore, when the signal amplitude drops to an amplitude that is between lines 210 and 212, it can be determined that the signal is being affected by capacitor bank activation.
[049] In some implementations, a grid event signature can be defined based on historical signal characteristic values for signal 202 when no grid event is occurring and historical signal characteristic values for signals received by the channel when an event particular grid is taking place. For example, based on this, it can be determined that when a capacitor bank is activated and affects the signals that are received by the channel over which signal 202 is transmitted, signal 202 drops to an amplitude that is below the range of baseline signal value (as represented by lines 208 and 206) to the amplitude range between lines 210 and 212. Therefore, the amplitudes represented by lines 208, 212, and 210 can be used to define a grid event signature for a capacitor bank activation. Similarly, it can be determined that when the capacitor bank is turned off, signal 202 will again return to an amplitude that is between lines 208 and 206 (assuming no other grid events are affecting signal 202). Hence, the amplitudes that are represented by lines 212, 208, and 206 can be used to define a grid event signature for a capacitor bank off.
[050] Fig. 2B is a graph 220 of another exemplary signal 222 that may be received by a communications channel. Based on the above discussion, analysis of historical signal characteristic values for signal 222 can be used to determine that the average amplitude of signal 222 when no grid event is affecting signal 222 is represented by line 224, and that signal is generally (that is, with a statistical measurement of probability) within an amplitude range that is between lines 226 and 228. Analysis of historical signal characteristic values can also reveal that when signal 222 is affected by a power failure, signal 222 generically drops below the amplitude represented by line 232. In some implementations, the amplitude represented by line 232 is a threshold interrupt amplitude that is specifically based, at least in part, on the historical analysis of signal amplitudes during periods when outages were known to affect signals received by the channel or as specified by an r administrator it's from.
[051] Based on this, the amplitudes represented by lines 228 and 232 can be used to define a grid event signature for a power failure and/or a power restoration. For example, the grid event signature for a power failure can be defined so that signal 222 falling below the amplitude represented by line 228 and the amplitude represented by line 232 is indicative of the power failure (i.e., corresponds to grid event signature for power outage). In this example, an energy restoration event signature can be defined such that signal 222 rising from an amplitude that is below the amplitude represented by line 232 to an amplitude that is above the amplitude that is represented by line 228 be indicative of a power restoration (that is, match the grid event signature for power restoration).
[052] Figure 3 is a flowchart of an example process 300 to detect grid events. Process 300 is a process by which signal characteristic values for signals that are received over a communications channel are determined to be outside a baseline signal value range. The endpoint that communicates over the communications channel is identified, and a determination is made that the signal characteristic values correspond to a grid event signature for a particular grid event. Successively, data is provided that specifies the endpoint and the particular grid event.
[053] Process 300 can be implemented, for example, by SPU 104 and/or network management apparatus 118 of Figure 1. In some implementations, one or more processors are configured to perform actions of process 300 In other implementations, a computer-readable medium may include instructions that when executed by a computer cause the computer to perform actions of process 300. Process 300 is described with reference to the signals (e.g., symbols) that are received channels of a PLC network, but process 300 can also be implemented in other communications environments.
[054] Signal characteristic data specifying signal characteristic values is received for the signals (302). In some implementations, signal characteristic values are received for each communications channel over which the signals are received. For example, endpoints in a PLC network can transmit symbols over one or more than thousands of communications channels so that characteristic signal values can be received for thousands of different signals. As described in detail with reference to Figure 1, signal characteristic values may include signal amplitude edits, noise floor measurements, measurements between signal and noise, and/or frequency domain measurements.
[055] A determination is made whether a signal characteristic value for signals that are received by a communications channel is outside a baseline signal value range (304). As described with reference to Figures 2A and 2B, the baseline signal value range for the signal characteristic value may be a range of values that have been determined to be indicative of a "normal" operating condition (e.g., periods during which operations such as communications between an SPU and endpoints are not substantially affected by grid events).
[056] The baseline signal value range for a signal amplitude measurement can be, for example, a range of values that are defined by a maximum acceptable amplitude for the baseline signal value range. minimum acceptable amplitude for the baseline signal value range. In this example, if the signal amplitude that is specified by the signal characteristic data is between the maximum acceptable amplitude and the minimum acceptable amplitude, the signal amplitude (that is, the signal characteristic value) is considered to be a state within the range of baseline signal amplitude. However, if the signal amplitude that is specified by the signal characteristic data is greater than the maximum acceptable amplitude or less than the minimum acceptable amplitude, the signal amplitude (ie, the signal characteristic value) is considered to be being outside the baseline signal amplitude range.
[057] In response to the determination that the signal characteristic value is not outside the baseline signal value range, the signal characteristic data continues to be received (302).
[058] In response to the determination that the signal characteristic value is outside the baseline signal value range, an endpoint that communicates over a channel to which the signal characteristic data has been received is identified (306) . In some implementations, the endpoint that communicates over the channel is identified using an index (or other data organization structure) that includes a list of endpoint identifiers for endpoints that communicate over the channels. on the network and communications channels to which each of the endpoints communicate. For example, as described above, each communications channel can be stored in an index location for the endpoint and/or stored with an endpoint reference. Thus, the endpoint that communicates over a particular communications channel can be identified by searching the index for a reference to the communications channel, and identifying the endpoint to which the communications channel is indexed.
[059] A determination is made whether a set of signal characteristic values corresponds to a grid event signature (308). The set of signal characteristic values may include, for example, a set of signal characteristic values for a single signal characteristic (eg, a set of signal amplitudes), where the set of signal characteristic values in- includes values that were received during a specified period (for example, one or more unit intervals). Alternatively, the set of signal characteristic values may specify a set of signal characteristic values for multiple different signal characteristics and/or which have been received during a specified period.
[060] Determining whether the signal characteristic values match a grid event value is made by comparing the set of signal characteristic values to the grid event signature to determine if a match exists. In some implementations, there is a correspondence when the signal being received has a signal characteristic value (eg, signal amplitude) that changes by a threshold amount and/or within a threshold time period. For example, as described above with reference to Figures 2A and 2B, when the signal amplitude of a signal falls below a minimum amplitude of a baseline signal value range and below a threshold indicative of a power failure, the set of signal characteristic values can be determined to have matched the grid event signature for a power failure. Therefore, the endpoint can be determined to be affected by a power outage.
[061] In some implementations, there are multiple grid event signatures, where each of the grid event signatures is indicative of a particular grid event. For example, grid event signatures can exist for each among a capacitor bank failure, a power outage, a capacitor bank activation, and/or other grid events (eg, a reclose failure). The set of signal characteristic values can be compared to each of the grid event signatures to determine whether the set of signal characteristic values matches any of the grid event signatures.
[062] In some implementations, the grid event subscription for a single grid event may vary on a per-channel and/or per-end point basis. For example, different signal thresholds and/or timing parameters (ie, periods of time between a signal transition between two amplitudes of a grid event signature) can be used to define the same grid event. to two different communication channels and/or two different endpoints. As described above, each grid event signature can be determined based on statistical analysis (and/or machine learning) of historical signal characteristic values for signals that are received under normal operating conditions and historical signal characteristics for signals which are received during periods when the endpoint and/or the communications channel over which the endpoint communicates has been affected by a grid event.
[063] When it is determined that the set of signal characteristic values does not correspond to a grid event signature, the signal characteristic data may continue to be received (302).
[064] When it is determined that the set of signal characteristic values does not match a grid event signature, the data identifying the endpoint and grid event to which the matched grid event signature is indicative are provided (310). In some implementations, the data may also specify the network element that is contributing to the grid event ("contributing network element"), a geographic location of the contributing network element, and/or a current state (eg open or closed or enabled or disabled) for the contributing network element.
[065] As described in more detail with reference to Figure 4, the location of a network element that may be the source of the grid event (i.e., the contributing network element) can be identified based on the locations of the points of affected endpoints and/or interconnections between network elements. For example, assuming the grid event is identified as a switch close failure, the network configuration can be analyzed to determine the location of a switch that has at least a threshold probability of being malfunctioning (by example, based on the locations of the affected endpoints and the electrical interconnections between the affected endpoints).
[066] Status data that has been received from the network element can specify a reported state that differs from the current state of the network element. Continuing with the previous example, if the status reported for the switch is open, a determination that the reported status of the network element is inaccurate can be made based on the determination that the signal value characteristics for the point of affected end are indicative of (that is, correspond to a grid event signature of) a closed switch. In this example, the data that is provided can specify that the switch may be the cause of the grid event, and/or that the current state of the network element is closed, and that the current state differs from the reported state.
[067] Figure 4 is a flowchart of an example process 400 to identify the endpoints that are affected by a grid event. Process 400 is a process by which map data specifying geographic locations of endpoints (or other network elements) is used to identify a geographic location of an endpoint that has been determined to be affected by a grid event as well as a set of endpoints that are likely to be affected by the grid event. Signals being received from endpoints in the endpoint set are analyzed to determine if endpoints are also being affected by the grid event. Successively, a particular endpoint in the set (or another endpoint or network element) is identified as the endpoint that contributes (for example, is causing at least part of) the grid event that is affecting the points of end. Data is provided that specifies the endpoint that is contributing to the grid event, for example, to a user device.
[068] Process 400 can be implemented, for example, by the SPU 104 and/or the network management apparatus 118 of Figure 1. In some implementations, one or more processors are configured to perform actions of process 400. In other implementations , a computer-readable medium may include instructions that when executed by a computer cause the computer to perform actions of process 400. Process 400 is described with reference to endpoints that are implemented in a PLC network, but process 400 is also it can be implemented for other network elements and/or in other communications environments.
[069] Map data specifying the geographic locations of endpoints (and other network elements) is accessed (402). In some implementations, geographic location can be represented by a latitude/longitude pair that represents the location at which the endpoint is installed in a powerline communications network. For example, the map data can specify the geographic coordinates for each meter, each utility pole, each substation, each switch, each transformer, each capacitor bank, as well as other network elements that are installed in the PLC network.
[070] Map data can also specify the configuration of endpoints and other network elements in the PLC network. For example, map data can include element interconnect data that specifies, for an endpoint, each network element to which the endpoint is connected, characteristics of the electrical connection between the network elements (e.g. connection impedance, electrical connection length, and/or other characteristics), utility pole locations.
[071] In some implementations, map data can be used to provide data that induces a presentation on a user device of the relative locations of network elements as well as the electrical and/or physical connections between the elements network. For example, data that induces the presentation of a map and icons representing each network element can be provided to the device used. The data can induce the user device to present the icons for each network element in a map location that represents the geographic location of the network element, and can also induce the presentation of text and/or graphics that allow a user to distinguish and/or uniquely identify each of the network elements. Map data can be accessed, for example, from a data store such as map data store 122 of Figure 1.
[072] Using map data, a geographic location of an endpoint (or other network element) that is affected by a particular grid event is determined (404). In some implementations, the endpoint that is affected by a particular grid event is identified using a process similar to that described with reference to Figure 3. Alternatively, the endpoint that is affected by a grid event can be reported by a customer or service technician.
[073] In some implementations, the geographic location of the endpoint is identified by fetching the map data for an endpoint identifier reference for the affected endpoint. For example, if the map data for each endpoint is indexed according to the endpoint identifier for the endpoint, the geographic location of an affected endpoint can be obtained by locating the endpoint identifier. endpoint to endpoint, and identifying the geographic location that is indexed to the endpoint identifier for the affected endpoint.
[074] A set of network elements that are within a threshold distance from the geographic location of the affected endpoint is identified (406). In some implementations, the threshold distance can be specified as an absolute distance (eg, 4.8 km (3 miles)) from the affected endpoint or a relative distance from another location. Threshold distance can be specified, for example, by a network administrator and/or based on an analysis of previous grid events and relative locations of the network elements that were affected by the grid event.
[075] In some implementations, the set of network elements that are identified may be restricted based on the configuration of the network elements and the location of the affected endpoint. For example, candidate network elements for the set of network elements (that is, network elements that are within the threshold distance from the affected endpoint) can be excluded from the set if the candidate network elements are not electrically coupled to the affected endpoint or the same network element as the affected endpoint. For example, if the affected endpoint has been determined to be affected by a power outage, candidate network elements that are within the threshold distance from the affected endpoint, but do not receive power from the same substation, through the same set of conductors (ie, power lines), through the same transformers, or through other network elements that may be excluded from the set of network elements.
[076] A determination can be made that one or more of the network elements in the set are also being affected by the particular grid event (408). In some implementations, a determination can be made based on at least one location of one or more network elements, the location of the affected endpoint, the physical and/or electrical configuration of one or more network elements, and the point affected extremity, and/or in the event of a particular grid. As described above, the configuration (eg, electrical interconnections) of network elements can be indicative of the probability that particular grid events will affect the network elements. For example, the probability that network elements that are electrically isolated from each other (eg, through a switch that is currently open, a substation, or other network element that electrically isolates the network elements) will affect -affected by the same grid event is less than the probability that two network elements that are electrically connected to the same transformer will be affected by the same grid event.
[077] In some implementations, one or more network elements in the set that are also being affected by the particular grid events are identified using a process similar to that described with reference to Figure 3. For example, a set of characteristic signal values for each of the network elements in the set can be compared to the grid event signature for the particular event. Successively, one or more network elements to which the set of signal characteristic values corresponds to the grid event signature for the particular grid event are determined to be affected by the particular grid event.
[078] A particular network element from the set that is configured to grid event is identified (410). As described earlier, electrical interconnections between network elements can affect the probability that a particular element is the cause (or the partial cause) of the grid event (ie, the contributing network element). For example, network elements that are electrically isolated from the affected endpoint (and/or other affected network elements) are unlikely to be the cause of the grid event that is affecting the affected endpoint.
[079] Similarly, the type of grid event that is affecting the affected endpoint (and/or other affected network elements) affects the probability that particular network elements are the cause of the grid event. For example, if the grid event is determined to be a capacitor bank failure, a transformer is unlikely to be the contributing network element. Therefore, the set of network elements can be filtered to remove network elements that have a lower threshold probability of being the contributor based on the type of grid event being experienced and/or the configuration of the network elements. Filtering the set of network elements results in fewer potential contributing network elements remaining, so the level of confidence with which the contributing network element is identified is greater than the level of confidence with which an element is identified. network elements can be selected from the full set of network elements.
[080] Data that prompts to specify the particular endpoint that is contributing to the grid event is provided (412). In some implementations, the data that is provided may also induce the presentation of a map interface that visually identifies a geographic location of the contributing network element and/or the grid event to which the network element is contributing. For example, if a particular switch is malfunctioning, as described above, an icon representing a switch may be presented on a map location that represents the switch's geographic location.
[081] In some implementations, the data also induces a visual indication that the switch is malfunctioning. Visual indication may include highlighting the switch, inducing the icon for the switch to flash, or otherwise visually emphasizing the icon for the switch over other icons representing other network elements. The data can also cause icons for the network elements that are being affected by the grid event to be visually emphasized. The visual emphasis of the affected network elements may differ from the visual emphasis of the contributing network element, for example, so that the contributing network element is visually identifiable by a user.
[082] In some implementations, the signal characteristic values that are received from the network elements continue to be monitored to determine if additional network elements are being affected by the grid event. In response to the determination that additional network elements are being affected by the grid event, the map interface can be updated to visually identify the geographic locations of the newly affected network elements.
[083] Figure 5 is a block diagram of an exemplary system 500 that can be used to facilitate grid event detection, as described above. System 500 includes a processor 510, a memory 520, a storage device 530, and an input/output device 540. Each of the components 510, 520, 530, and 540 can be interconnected, for example, using a 550 system bus. The 510 processor is capable of processing instructions for execution within the 500 system. In one implementation, the 510 processor is a uni-threaded processor. In another implementation, the 510 processor is a multithreaded processor. The processor 510 is capable of processing instructions stored in memory 520 or a storage device 530.
[084] Memory 520 stores information within system 500. In one implementation, memory 520 is a computer-readable medium. In one implementation, memory 520 is a unit of volatile memory. In another implementation, the 520 memory is a non-volatile memory unit.
[085] Storage device 530 is capable of providing mass storage for system 500. In one implementation, storage device 530 is a computer-readable medium. In several different implementations, storage device 530 may include, for example, a hard bait device, an optical disk device, or some other large-capacity storage device.
[086] Input/output device 540 provides input/output operations for system 500. In one implementation, input/output device 540 may include one or more of a network interface device, per example, an Ethernet card, a serial communication device, for example, and an RS-232 port, and/or a wireless interface device, for example, and an 802.11 card. In another implementation, the input/output device may include driver devices configured to receive input data and send output data to other input/output devices, for example, keyboard, printer, and 560 display devices. implementations can also be used, such as mobile computing devices, mobile communication devices, television signal decoding client devices, etc.
[087] Although an exemplary processing system has been described in Figure 5, the subject implementations and functional operations described in this specification can be implemented in other types of digital electronic circuits, or in computational software, firmware, or hardware , including the structures disclosed in this descriptive report and their structural equivalents, or in combinations of one or more of these.
[088] The subject modalities and operations described in this descriptive report can be implemented in digital electronic circuits, or in computer software, firmware, or hardware, including the structures disclosed in this descriptive report and their structural equivalents, or in combinations of one or more of these. The subject modalities described in this descriptive report can be implemented as one or more computer programs, that is, one or more computer program instruction modules, encoded in a computer storage medium for executing, or controlling the operation, of the apparatus of data processing. Alternatively or additionally, the program instructions may be encoded in an artificially generated propagated signal, for example, a machine-generated electrical, optical or electromagnetic signal, which is generated to encode information for transmission to a suitable receiving apparatus for performed by a data processing apparatus. A computational storage medium can be, or be included in, a computer readable storage device, a computer readable storage substrate, a serial or random access memory array or device, or a combination of one or more of these. Furthermore, although a computational storage medium is not a propagated signal, a computational storage medium can be a source or a destination of computational program instructions encoded in an artificially generated propagated signal. The computational storage medium can also be, or be included on, one or more separate physical components or media (eg, multiple CDs, disks, or other storage devices).
[089] The operations described in this descriptive report may be implemented as operations performed by a data processing apparatus on data stored in one or more computer-readable storage devices or received from other sources.
[090] The term "data processing apparatus" encompasses all types of apparatus, devices, and machines for data processing, including by way of example a programmable processor, a computer, a system on a chip, or in multiples, or combinations thereof. The apparatus may include special purpose logic circuitry, for example, an FPGA (Field Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit). The apparatus may also include, in addition to hardware, codes that create an execution environment for the computer program in question, for example, a code that constitutes a processor firmware, a protocol stack, a database management system, an operating system, a cross-platform runtime environment, a virtual machine, or a combination of one or more of these. The appliance and the execution environment can realize many different computational model infrastructures, such as web services, distributed computational infrastructures, and grid computational infrastructures.
[091] A computer program (also known as a program, software, software application, script, or code) may be written in the form of a programming language, including compiled or interpreted languages, declarative or procedural languages, and may be deployed in any form, including as a stand-alone program or as a module, component, subroutine, object, or other unit suitable for use in a computing environment. A computer program can, but need not, correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs or data (for example, one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in multiples coordinated files (for example, files that store one or more modules, subprograms, or pieces of code). A computer program can be deployed to run on one computer or on multiple computers that are located at one site or at multiple sites and interconnected by a communication network.
[092] The logical processes and flows described in this descriptive report can be performed by one or more programmable processors executing one or more computer programs to perform actions operating on input data and generating an output. Logic flow processes can also be performed by, and apparatus can also be implemented as, special purpose logic circuits, for example, an FPGA (Field Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit).
[093] Processors suitable for executing a computer program include, by way of example, microprocessors for general and special purposes, and any one or more processors of any type of digital computer. In general, a processor will receive instructions and data from read-only memory or random access memory, or both. The essential elements of a computer consist of a processor to carry out actions according to instructions and one or more memory devices to store instructions and data. In general, a computer will also include, or be operatively coupled to receive data or transfer data, or both, to one or more mass storage devices for storing data, for example, magnetic, magneto-optical, or optical disks. However, a computer does not need to have such devices. In addition, a computer can be built into another device, for example, a mobile phone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a Global Positioning System (GPS) receiver, or a portable storage device (for example, a universal serial bus (USB) flash drive), just to name a few. Devices suitable for storing computer program instructions and data include all forms of non-volatile memory, media and memory devices, including, by way of example, semiconductor memory devices, eg EPROM, EEPROM, and flash memory devices; magnetic disks, for example internal hard disks or removable disks; magneto-optical discs; and CD-ROM and DVD-ROM discs. Processor and memory can be supplemented by, or incorporated into, special-purpose logic circuits.
[094] To provide interaction with a user, the subject modalities described in this descriptive report can be implemented on a computer having a display device, for example, a CRT (cathode ray tube) or LCD (screen) monitor crystal) to display information to the user and a keyboard and pointing device, for example, a mouse or track-ball, through which the user can provide input to the computer. Other types of devices can be used to provide interaction to a user; for example, the feedback provided to the user can be any form of feedback, for example, visual feedback, auditory feedback, or tactile feedback; and input from the user can be received in any form, including acoustic, speech, or tactile input. In addition, a computer can interact with a user by sending documents to and receiving documents from a device that is used by the user; for example, sending web pages to a web browser on a user's client device in response to requests received from the web browser.
[095] Although this descriptive report contains many specific implementation details, these should not be construed as limitations on the scope of any inventions or what can be claimed, but rather descriptions of features specific to particular modalities of inventions private individuals. Certain features that are described in this descriptive report in the context of separate modalities can also be implemented in combination in a single modality. Conversely, multiple features that are described in the context of a single modality can also be implemented in multiple modalities separately or in any suitable subcombination. Furthermore, although features may be described above acting in certain combinations and even initially claimed as such, one or more features of a claimed combination may in some cases be removed from the combination, and the claimed combination may be directed to a sub-combination or variation of a subcombination.
[096] Similarly, although operations are described in the drawings in a particular order, they are not to be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed , to achieve the desired results. In certain circumstances, multi-tasking and parallel processing can be advantageous. Furthermore, the separation of various system components in the modalities described above should not be understood as requiring such separation in all modalities, and it should be understood that the described components and program systems can be generically integrated together in a single product software or bundled into multiple software products.
[097] Then, the particular modalities of the subject were described. Other modalities are within the scope of the following claims. In some cases, the actions cited in the claims may be carried out in a different order and still achieve desirable results. Furthermore, the processes described in the attached figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In certain implementations, multitasking and parallel processing can be advantageous.

权利要求:
Claims (16)
[0001]
1. Method performed by a data processing apparatus (104, 118), CHARACTERIZED in that it comprises: receiving (302), by the data processing apparatus (104, 118), characteristic signal data specifying characteristic values of signal for signals that are received via each of a plurality of communication channels of a power line communication network (101) to communicate data over the power line network; determining (304) by the data processing apparatus (104, 118) that the signal characteristic values for the signals that are received through at least one of the communications channels are outside a range of a line signal value of base; to communicate data over the power line network (101), identifying (306) an endpoint (102) that communicates over the at least one communications channel; determine (308) that a set of signal characteristic values correspond to one of a plurality of grid event signatures for the identified endpoint (102), each of the grid event signatures being indicative of a particular grid, wherein the plurality of grid event signatures include a respective grid event signature for each of a set of grid events including a capacitor bank failure (112), a power outage, and activation of capacitor bank (112), and wherein determining (308) that the set of signal characteristic values corresponds to one of a plurality of grid event signatures, comprises determining that the set of signal characteristic values corresponds to a signature of grid event for one of a capacitor bank failure (112), a power outage, or a capacitor bank activation (112); and providing (310) data identifying the endpoint (102) and the particular grid event to the grid event signature that is matched by the set of monitored signal characteristics.
[0002]
2. The method of claim 1, CHARACTERIZED in that identifying an endpoint (102) that communicates over the communications channel comprises identifying an endpoint identifier for the endpoint (102) that communicates. communicates over the communications channel, the endpoint identifier being identified from an index of endpoint identifiers for endpoints and communications channels through which each of the endpoints communicate.
[0003]
3. Method according to claim 1, CHARACTERIZED in that it further comprises: accessing (402) map data specifying geographic locations of endpoints (102); and determining (404) a geographic location of the identified endpoint (102) based on the map data.
[0004]
4. Method according to claim 3, CHARACTERIZED in that it further comprises: identifying (406) network elements (112, 114) that are within a threshold distance of the geographic location of the identified endpoint (102); and identifying (410) a particular network element in the set of network elements (112, 114) that is contributing to the grid event, the identification being based on at least one of the location of the identified endpoint (102), the location of the particular network element, or the particular grid event.
[0005]
5. Method according to claim 4, characterized in that it further comprises determining (408) that one or more additional network elements (102, 112, 114) in the set of network elements (102, 112, 114) are also affected by the particular grid event.
[0006]
6. Method according to claim 5, CHARACTERIZED in that determining (408) that one or more additional network elements (102, 112, 114) are also being affected by the particular grid event, comprises: for each the one or more additional network elements (102, 112, 114): comparing a set of characteristic signal values for the network element (102, 112, 114) with the grid event signature for the grid event particular; and determining that the set of signal characteristic values corresponds to the grid event signature.
[0007]
7. Method according to claim 5, CHARACTERIZED in that it further comprises providing data that cause the presentation of a map interface that visually identifies a geographic location of the network element (102, 112, 114) that is contributing to the particular grid event and a geographic location of the one or more additional network elements that are also being affected by the particular grid event.
[0008]
8. The method of claim 7, CHARACTERIZED in that it further comprises updating the map interface in response to the determination that a new network element (102, 112, 114) has been determined to be one of the one or more additional network elements, the map interface being updated to visually identify the geographic location of the new network element (102, 112, 114).
[0009]
9. Method according to claim 1, characterized in that it further comprises: receiving status data from a network element (102, 112, 114) specifying a reported state of the network element; determining, based on the received signal characteristic values, that the status data from the network element (102, 112, 114) is invalid; and providing data specifying a current state of the network element (102, 112, 114).
[0010]
10. Method according to claim 1, CHARACTERIZED by the fact that the signal characteristic values include at least one of a peak amplitude, a minimum amplitude, a maximum amplitude, duty cycle, and a frequency measure of the signals that are received over the plurality of communications channels.
[0011]
11. Computer-readable storage media CHARACTERIZED by the fact that it stores a method as defined in any of the preceding claims.
[0012]
12. System, CHARACTERIZED in that it comprises: a plurality of network elements (102, 112, 114) that are implemented in a power line communications network (101); and one or more data processing apparatus (104, 118) operable to interact with the network elements, the one or more data processing apparatus (104, 118) being further operable to perform operations including: receiving, by the apparatus data processing (104, 118), signal characteristic data specifying signal characteristic values for signals that are received by each of a plurality of communications channels of the power line communications network (101); determining, by the data processing apparatus (104, 118), that the signal characteristic values for the signals that are received via at least one of the communications channels are outside a baseline signal value range; identifying an endpoint (102) that communicates over the at least one communications channel; determining that a set of signal characteristic values correspond to one of a plurality of grid event signatures for the identified endpoint (102), each of the grid event signatures being indicative of a particular grid event; and wherein the plurality of grid event signatures includes a respective grid event signature for each of a set of grid events including a capacitor bank failure (112), a power outage, and an activation of capacitor bank (112), and wherein determining that the set of signal characteristic values corresponds to one of a plurality of grid event signatures comprises determining that the set of signal characteristic values corresponds to an event signature from grid to one of a capacitor bank failure (112), a power outage, or a capacitor bank trip (112); and providing data identifying the endpoint (112) and the particular grid event to the grid event signature that is matched by the set of monitored signal characteristics.
[0013]
13. System according to claim 12, CHARACTERIZED by the fact that the system further comprises a user device (118) that is operable to interact with the one or more data processing apparatus (104, 118), the device user (118) being further operable to perform operations including receiving the data identifying the endpoint (102) and causing a reference to the identified endpoint (102) to be presented.
[0014]
14. System, according to claim 12, CHARACTERIZED by the fact that the one or more data processing devices (104, 118) are still operable to perform operations that include: identifying an endpoint identifier for the endpoint (102) that communicates over the communications channel, the endpoint identifier being identified from an index of endpoint identifiers for endpoints and communications channels through which each of the endpoints communicate; accessing map data that specify geographic locations of endpoints (102); and determining a geographic location of the identified endpoint (102) based on the map data.
[0015]
15. System, according to claim 14, CHARACTERIZED by the fact that the one or more data processing devices (104, 118) are still operable to perform operations that include: identifying the network elements (102, 112 , 114) that are within a threshold distance from the geographic location of the identified endpoint (102); and identifying a particular network element (102, 112, 114) in the set of network elements that is contributed to the grid event, the identification being based on at least one of the location of the identified endpoint (102) , the location of the particular network element (102, 112, 114), or the particular grid event.
[0016]
16. System, according to claim 15, CHARACTERIZED by the fact that the one or more data processing devices (104, 118) are still operable to perform operations that include: determining that one or more network elements ( 102, 112, 114) additional in the set of network elements are also being affected by the particular grid event; and providing data causing presentation of a map interface that visually identifies a geographic location of the network element (102, 112, 114) that is contributing to the particular grid event and a geographic location of the one or more network elements (102, 112, 114) additional who are also being affected by the particular grid event.

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法律状态:
2020-09-29| B06U| Preliminary requirement: requests with searches performed by other patent offices: procedure suspended [chapter 6.21 patent gazette]|

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2020-10-06| B06F| Objections, documents and/or translations needed after an examination request according [chapter 6.6 patent gazette]|

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2021-03-16| B09A| Decision: intention to grant [chapter 9.1 patent gazette]|

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2021-05-04| B16A| Patent or certificate of addition of invention granted|Free format text: PRAZO DE VALIDADE: 20 (VINTE) ANOS CONTADOS A PARTIR DE 09/03/2012, OBSERVADAS AS CONDICOES LEGAIS. |

优先权:

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申请号 | 申请日 | 专利标题

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US13/075,646|US8693580B2|2011-03-30|2011-03-30|Grid event detection|

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US13/075,646|2011-03-30|

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PCT/US2012/028587|WO2012134772A1|2011-03-30|2012-03-09|Grid event detection|

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