System and method of compiling and organizing power consumption data and converting such data into one or more user actionable formats

Abstract

A method and system for use in creating a profile of, managing and understanding power consumption in a premise of a user, wherein said premise comprises two or more power consuming devices comprises measuring, via at least one sensor, aggregate energy consumption at the premise, receiving at a mobile computing device comprising a data processor, said aggregated signal from the sensor, collecting and recording the aggregate signal over a plurality of time resolutions and frequencies, therein to create a predicted aggregate signal for each time x and frequency y, detecting changes in the predicted aggregate signal at time x an frequency y (detected consumption pattern changes) and conveying to at least one of the user, a utility company, and other third party a notification of detected consumption pattern changes.

Description

FIELD OF THE INVENTION[0001]The present invention relates to the field of granular power monitoring, data analytics and enhanced data use at both the consumer and industry levels.BACKGROUND OF THE INVENTION[0002]Energy management is a term that generally relates to or is implemented by systems, processes and devices in order to reduce energy consumption and understand energy consumption patterns. This can occur in private homes, in businesses, in factories / manufacturing facilities and in public-sector / government organizations, to name a few.[0003]From the perspective of an energy consumer, the process of monitoring, controlling, and conserving energy in a building or organization typically involves the following steps, with noted challenges and limitations:[0004]1. Metering (in some fashion) energy consumption and collecting the data.[0005]2. Understanding the raw data and / or collecting data that is useful.[0006]3. Finding opportunities to save energy, and estimating how much energy...

AI Technical Summary

Benefits of technology

[0070]As such the data analytics in accordance with the present invention yield superior demand forecasts by “segmenting” user profiles and modeling their consumption behavior separately using increased input data granularity. With access to real time segmented data, accurate short term (and long term) demand projections are made more accurately which affords significant cost saving to a utility and ultimately to a consumer, whether that consumer be a family, a business or a manufacturing operation.

Problems solved by technology

This is not only onerous but of very limited use in terms of data spread.

The problem is that people do not want to incur the significant expense required to install power sensors on each of their appliances and electric loads.

a) while there is some value to the bulk aggregate data, it is not the definitive picture in energy management, in fact, it barely scratches the surface of what should be possible and available to power consumers; and

b) load disaggregation or cataloguing power usage at a granular level is difficult to currently achieve. Even if power sensors are attached onto every single appliance in a home, there is still the issue of the value of the produced raw data without further enhancements and value added.

Furthermore, there is a growing tendency towards unbundling the power system as different sectors of the industry (generation, transmission, and distribution) are faced with increasing demand on planning management and operations of the networks.

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