Method and system for hvac inefficiency prediction using household electrical smart meter data

Abstract

A method for monitoring heating, ventilation, and air conditioning (HVAC) systems includes: Obtaining first training data for HVACs in a training set of households during a first period of spring weather; Obtaining second training data during a period of summer weather, Preprocessing the training data to identify repeating patterns of HVAC consumption or generating additional derived parameters, in an aggregation process; Calculating the amount of energy required to change house temperature; Applying the first training data and the classification labels to train a supervised machine learning algorithm, to generate an HVAC classification model predictive of inefficiency during periods of summer weather conditions; Obtaining operational data pertaining to HVACs in an operational set of households during a second period of spring weather; and Applying the HVAC classification model to predict inefficiency of HVACs at individual households in the operational set, during periods of summer weather using only overall household power consumption.