Time-Series Prediction: Application to the Short-Term Electric Energy Demand

This paper describes a time-series prediction method based on the kNN technique. The proposed methodology is applied to the 24hour load forecasting problem. Also, based on recorded data, an alternative model is developed by means of a conventional dynamic regression technique, where the parameters are estimated by solving a least squares problem. Finally, results obtained from the application of both techniques to the Spanish transmission system are compared in terms of maximum, average and minimum forecasting errors.

• Type: Conference
• Year: 2003
• Where: CAEPIA
• Authors: Alicia Troncoso Lora, Jesús Riquelme Santos, José Cristóbal Riquelme Santos, Antonio Gómez Expósito, José Luís Martínez Ramos
• Keywords: CAEPIA 2003, Dynamic Regression Technique, Load Forecasting Problem, Time-series Prediction Method