DETECTING ELECTRICITY THEFT VIA METER TAMPERING USING STATISTICAL METHODS
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Abstract
A system and method for detecting anomalous energy usage of building or household entities. The method applies a number of successively stringent anomaly detection techniques to isolate households that are highly suspect for having engaged in electricity theft via meter tampering. The system utilizes historical time series data of electricity usage, weather, and household characteristics (e.g., size, age, value) and provides a list of households that are worthy of a formal theft investigation. Generally, raw utility usage data, weather history data, and household characteristics are cleansed, and loaded into an analytics data mart. The data mart feeds four classes of anomaly detection algorithms developed, with each analytic producing a set of households suspected of having engaged in electricity theft. The system allows a user to select households from each list or a set based on the intersection of all individual sets.
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Citations
24 Claims
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1-10. -10. (canceled)
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11. A system for detecting anomalous energy usage amongst building and household entities, said system comprising:
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a data storage device; a processor unit coupled to the data storage device configured to perform a method to; receive, at a computing system, data comprising energy usage data relating to a building'"'"'s actual energy use over a defined time period, characteristics data of the building, and weather data over one or more defined time periods; cluster buildings in one or more clusters as determined based on a building'"'"'s energy usage in each time period; identify buildings having energy usage that migrate from one cluster to another cluster between time periods, generate a model to predict a building'"'"'s energy usage, said model defining expected bounds of energy consumption given time of day (shift) and weather and building characteristics data received; compare energy usage for each building against an energy use predicted by the model for said building; and identify, from said comparison, buildings whose electricity usage is not predicted by model, wherein said buildings identified as migrating from one cluster to another cluster between time periods, and said buildings exhibiting electricity usage not predicted by said generated model are flagged as anomalous energy usage entities. - View Dependent Claims (12, 13, 14, 15, 16, 17)
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18. A computer program product for detecting anomalous energy usage amongst building and household entities, the computer program product comprising a tangible storage medium, said tangible storage medium excluding only propagating signals, said medium readable by a processing circuit and storing instructions run by the processing circuit for performing a method, the method comprising:
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receiving, at a computing system, data comprising energy usage data relating to a building'"'"'s actual energy use over a defined time period, characteristics data of the building, and weather data over one or more defined time periods; clustering buildings in one or more clusters as determined based on a building'"'"'s energy usage in each time period; identifying buildings having energy usage that migrate from one cluster to another cluster between time periods, generating a model to predict a building'"'"'s energy usage, said model defining expected bounds of energy consumption given time of day (shift) and weather and building characteristics data received; comparing energy usage for each building against an energy use predicted by the model for said building; and identifying, from said comparison, buildings whose electricity usage is not predicted by model; wherein said buildings identified as migrating from one cluster to another cluster between time periods, and said buildings exhibiting electricity usage not predicted by said generated model are flagged as anomalous energy usage entities. - View Dependent Claims (19, 20, 21, 22, 23)
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24-26. -26. (canceled)
Specification