Outage prevention in an electric power distribution grid using smart meter messaging
Abstract
A system and method is disclosed for using AMI smart meter messaging types and data mining decision trees to determine if local equipment failure is present. The system and method may be used to predict impending failure based upon smart meter message behaviors and to create proactive investigation tickets. The predictions models may be generated from a big database of smart meter messaging and customer outage reports. The system and method can be applied to detect failures of higher level device equipment and may be incorporated into customer service processes. The system and method may also be used to determine customer owned equipment failures for referral to electricians.
Claims
exact text as granted — not AI-modifiedWhat is claimed is:
1 . An electric power distribution system comprising:
an electric power distribution grid having a multiplicity of elements capable of becoming deficient; a multiplicity of smart meters coupling the electric power distribution grid and a corresponding multiplicity of premises, each smart meter measuring electric power consumed at each corresponding premises and generating a multiplicity of message types related thereto, the multiplicity of message types not including information specifying a deficient grid element; an automated meter infrastructure network coupled to the smart meters for communicating the messages from the smart meters; a message database coupled to the automated meter infrastructure network for receiving messages from the multiplicity of smart meters; an outage processor for receiving outage reports through a communication network different from the automated meter infrastructure network, each outage report associated with a failed deficient grid element; a model generator coupled to the message database for generating a multiplicity of models based upon the messages and the outage reports, each model identifying a defective grid element based upon a message behavior of a smart meter associated with the defective grid element, the message behavior including a plurality of messages of a plurality of message types received from the smart meter; a model selector for selecting a plurality of models from the multiplicity of models based upon a confidence factor; the message database for receiving additional messages after selection of the plurality of models; an outage predictor for processing the additional messages with the plurality of models to predict a likelihood of an outage at a suspect premise; and a ticket generator for generating a ticket enabling a repair crew to repair a deficient grid element associated with the suspect premises.
2 . The electric power distribution system according to claim 1 wherein the model generator generates C5.1 and CHAID decision tree models.
3 . The electric power distribution system according to claim 1 wherein the model selector determines a confidence level for each of the multiplicity of models and selects the plurality of models based upon the confidence level exceeding a threshold.
4 . The electric power distribution system according to claim 3 wherein the confidence level corresponds to 75%.
5 . The electric power distribution system according to claim 1 wherein the model generator generates C5.1 and CHAID decision trees having nodes corresponding to models and the model selector determines a confidence level for each of the nodes and selects the plurality of models based upon the confidence level of a corresponding node exceeding a threshold.
6 . The electric power distribution system according to claim 1 wherein the model generator scrubs the messages prior to generating the model.
7 . The electric power distribution system according to claim 6 wherein the model generator scrubs the messages by at least one of eliminating duplicate messages, selecting messages of a predetermined message type, and selecting messages according to a rate of occurrence of the message.
8 . The electric power distribution system of claim 1 , wherein the messages include at least one of:
a Network Interface Card Based Power Fail Detect Disabled message; a History of Direct Current Detected message; a Network Interface Card Power Down message; a Service Error Cleared message; a Zero Voltage Read message; and a Last Gasp message.
9 . A method for maintaining an electric power distribution grid comprising:
predicting an outage at a suspect premises based upon a message behavior of a multiplicity of messages generated by a smart meter coupling the electric power distribution grid and the suspect premises; and generating a repair ticket based upon the predicting.
10 . The method according to claim 9 wherein the multiplicity of messages have a multiplicity of message types and the message behavior includes a plurality of the multiplicity of messages having a plurality of the multiplicity of message types.
11 . The method according to claim 10 wherein the predicted outage at the suspect premises would result from a deficient element in the electric power distribution grid and the plurality of the multiplicity of messages do not include information specifying the deficient element.
12 . The method according to claim 10 wherein the message behavior includes a ratio of first messages over second messages, the first messages including a first message type and the second messages including the first message type and at least a second message type, the ratio being greater than zero and less than one.
13 . The method according to claim 10 wherein the message behavior excludes messages of the multiplicity of messages occurring beyond a time period.
14 . The method of claim 10 wherein the multiplicity of message types include:
a Network Interface Card Based Power Fail Detect Disabled message;
a History of Direct Current Detected message;
a Network Interface Card Power Down message;
a Service Error Cleared message;
a Zero Voltage Read message; and
a Last Gasp message.
15 . The method according to claim 9 wherein the predicting occurs before an occurrence of the outage at the suspect premises.
16 . The method according to claim 9 wherein the predicting occurs after an occurrence of the outage at the suspect premises, and the generating the repair ticket occurs before receiving an outage notice associated with the suspect premises, the outage notice being independent of the multiplicity of messages generated by the smart meter.
17 . The method according to claim 9 further comprising
determining the message behavior by generating a plurality of prediction models based upon a message database generated by a multiplicity of smart meters associated with a multiplicity of premises and an outage report database of associated with the multiplicity of premises, and
the predicting the outage at the suspect premises analyzes the multiplicity of messages with at least one of the plurality of prediction models to predict a likelihood of the outage at the suspect premises.
18 . The method according to claim 17 wherein the generating the plurality of prediction models includes generating a multiplicity of prediction models and selecting the plurality of prediction models from the multiplicity of prediction models based upon a confidence factor.
19 . The method according to claim 18 wherein the multiplicity of prediction models are generated based upon at least one of a C5.1 and a CHAID decision tree generation process.
20 . The method according to claim 9 wherein the suspect premises is included within a group of premises having a corresponding group of smart meters, the method further comprising predicting an absence of outages at a multiplicity of premises within the group of premises.
21 . The method according to claim 20 wherein the multiplicity of premises for which the absence of outages is predicted includes at least ninety nine point nine percent of the group of premises.
22 . The method according to claim 21 wherein the group of smart meters generate a big database within a time span, the group of smart meters comprising to at least six hundred thousand smart meters, the group of smart meters generating messages at an average rate of at least two messages per day per smart meter, the time span corresponding to twenty four hours.
23 . The method according to claim 9 wherein the predicting is made independent of any weather information specifying any weather condition to which the electric power distribution grid may be exposed.
24 . The method according to claim 9 wherein the repair ticket includes information identifying the suspect premises.
25 . The method according to claim 24 wherein the predicted outage at the suspect premises would result from a deficient element in the electric power distribution grid and the repair ticket includes information identifying the deficient element.
26 . The method according to claim 9 wherein a non-transitory computer-readable storage media stores instructions for a computer to perform the predicting, and a ticket output device coupled to the computer generates a humanly observable repair ticket indicative of the predicting.
27 . A non-transitory computer readable storage medium storing instructions for a computer to perform a method for maintaining an electric power distribution grid, the method comprising:
processing messages generated by a multiplicity of smart meters coupling the electric power distribution grid to a corresponding multiplicity of premises; processing outage tickets having information regarding outages experienced by at least a portion of the multiplicity of premises, the outage tickets being independent of the messages; generating a multiplicity of prediction models based upon the processing of the messages and the outage tickets, the prediction models predicting a likelihood of outages based on messages from smart meters; and selecting a message behavior from the multiplicity of prediction models, the message behavior for predicting an outage at a suspect premises based upon a multiplicity of messages generated by a smart meter coupling the electric power distribution grid and the suspect premises.
28 . The non-transitory computer readable storage medium of claim 27 wherein the predicted outage at the suspect premises would result from a deficient element in the electric power distribution grid and the selected message behavior does not include messages having information specifying the deficient element.
29 . The non-transitory computer readable storage medium of claim 27 wherein the multiplicity of prediction models are generated based upon at least one of a C5.1 and a CHAID decision tree generation process.
30 . The non-transitory computer readable storage medium of claim 27 wherein the message behavior includes a plurality messages having a plurality of message types.
31 . The non-transitory computer readable storage medium of claim 30 wherein the message behavior includes a ratio of first messages over second messages, the first messages including a first message type and the second messages including the first message type and at least a second message type, the ratio being greater than zero and less than one.
32 . The non-transitory computer readable storage medium of claim 30 wherein the message behavior excludes messages of the multiplicity of messages occurring beyond a time period.
33 . The non-transitory computer readable storage medium of claim 30 wherein the plurality of message types include at least two of:
a Network Interface Card Based Power Fail Detect Disabled message;
a History of Direct Current Detected message;
a Network Interface Card Power Down message;
a Service Error Cleared message;
a Zero Voltage Read message; and
a Last Gasp message.
34 . The non-transitory computer readable storage medium of claim 30 further comprising:
predicting the outage at the suspect premises; and
generating a repair ticket based upon the predicting.Join the waitlist — get patent alerts
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