Electricity price forecasting using Wavelet domain and Time domain features in a Regression based technique
نویسندگان
چکیده
A combined wavelet transform (WT) and multiple linear regression (MLR) based technique to forecast price profile in a single settlement real time electricity market has been presented. The historical price and load data has been decomposed into better-behaved wavelet domain constitutive subseries using WT and then combined with other time domain variables to form the set of input variables for the MLR based forecasting model, which models each day using 24 separate equations for 24 hours of the day. Forecasting performance of the proposed model for a period of three years has been compared with the three other models.
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