Method and system for forecasting building power consumption

Abstract

Power consumption forecasting plays a key role in the efficient operation of a building energy management system to assess energy demands of building, and at the same time, help electrical utilities in planning their supply operations. However, no state-of-the-arts are available for forecasting medium-term or long-term power consumption of the buildings. This disclosure relates to a method and system for forecasting a power consumption of buildings for a scalable forecast horizon. The system is configured to pre-process to deal with outliers/missing values, followed by synchronization of smart meter data with other sensory data. An energy-temperature correlation is calculated to estimate an energy drift using historical power consumptions. Further, in feature derivation stage, additional features necessary for the forecast are derived. The system is to be employed for modeling the building load consumption that depends on the time horizon of forecasting and the granularity of the data.