Systems and methods for interval energy disaggregation utilizing machine learning

Abstract

Systems and methods for interval energy disaggregation utilizing machine learning are provided. An example method includes obtaining and cleaning weather data and customer data, and based on the customer data, determining whether a structure utilizes solar energy. If the structure utilizes solar energy, the overall aggregate data is disaggregated by using and training a first machine learning model, to ultimately produce a predicted solar production. The predicted solar production is extracted from an overall aggregate data of the structure. Then, the method continues with disaggregating the non-solar aggregate data by utilizing at least a second ML model, to produce disaggregated data relating to at least one of AC energy consumption and EV (electric vehicle) consumption. The disaggregated data is provided to the customer or utility. The disaggregated data comprises at least one of the predicted solar production, the AC energy consumption, and the EV consumption of the structure.

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