Automatic machine learning based prediction of baseline energy consumption

Abstract

The present solution, approach or method, including an end-to-end automated data pipeline for data ingestion, storage, analysis, deployment, and a machine learning model maintenance. The present solution, approach or method, which computes a baseline using machine learning methods, may help in the following ways. Accurate real time estimation may help evaluate the deviation in the actual energy consumption, effectively identifying underlying root causes for an increase in actual consumption, as compared to the estimated energy. Triangulating the time of day and place of high energy consumption results in quicker resolution. Accurately quantifying energy savings may be helpful. Forecasting energy consumption in the future, may enable planning for future energy needs. Energy saving calculations may be done by comparing actual consumption versus baseline predicted consumption based for a specific baseline period. This solution may offer a configurable machine learning model, which takes on energy consumption patterns.

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