PROGRESSIVE HUMIDITY FILTER FOR LOAD DATA FORECASTING

A method, via a processor, of forecasting energy usage including selecting a plurality of reference days with at least one feature matching a corresponding feature of a day to be forecasted and filtering the plurality of reference days with a humidity filter to identify at least one matching reference day. The at least one matching reference day is associated with a correlation coefficient greater than or equal to a minimum correlation coefficient, and a minimum number of humidity values within a range of corresponding humidity values of the day to be forecasted. The method also includes retrieving energy load values and corresponding temperature values corresponding to the at least one matching reference day, calculating a plurality of regression coefficients of a polynomial equation linking the temperature values to the energy load values, and calculating and storing a forecasted load value of the day to be forecasted according to the polynomial equation.