Patent Document ID: 9600773
Application ID: 14026695
Patent Flag: 1

Claim One:
1. A computer-implemented method for detecting anomalous energy usage amongst building and household entities, said method comprising: receiving, at a computing system, data comprising energy usage data relating to a building's actual energy use over a defined time period (shift), characteristics data of the building, and weather data over one or more defined time periods, said building characteristics data comprising one or more selected from the group consisting of: a physical size of the building, a number of floors, a number of occupants, building age, a number of bedrooms, a number of bathrooms, a type of heating fuel in use, a type of air conditioning in use, and a latitude and longitude coordinate of the building; 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 across time of day shifts, said identifying comprising: representing a series of data processing operations as a series of data processing nodes, a node representing a usage data source for obtaining said energy usage data for a building; performing, from said node, concurrent data processing operations as parallel paths according to a respective shift, each parallel path comprising a flow of operations comprising a linking of said node, a node representing a data aggregation operation for that shift and a node representing clustering operations for that shift; merging data operations at each parallel path to obtain a list of energy use migrations for that building; generating a model to predict a building's energy usage, said model defining expected bounds of energy consumption given a time period (shift) and said weather data 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 the model, said identifying comprising: performing, from said node representing a usage data source for a building, concurrent data processing operations as parallel paths according to a respective shift, each parallel path comprising a flow of operations comprising a linking of said node, a node for generating non-linear regression models of energy use data aggregation operation for that shift, a node of operations for detecting anomalous buildings for that shift, and a node of operations to rank a building's anomalous energy usage based on statistics computed for the number of times a household's usage is flagged as anomalous; and merging data operations at each parallel path to obtain a list of top buildings having anomalous energy usage; 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, and wherein a processing unit of said computer system is configured to perform said receiving, clustering, identifying of migrating buildings, model generating, comparing, and said identifying of buildings from said comparison.