Prediction of daily maximum temperature using a support vector regression algorithm

Publication year: 2011
Source: Renewable Energy, Volume 36, Issue 11, November 2011, Pages 3054-3060

A., Paniagua-Tineo , S., Salcedo-Sanz , C., Casanova-Mateo , E.G., Ortiz-García , M.A., Cony , …

Daily maximum temperature can be used a good indicator of peak energy consumption, since it can be used to predict the massive use of heating or air conditioning systems. Thus, the prediction of daily maximum temperature is an important problem with interesting applications in the energy field, since it has been proven that electricity demand depends much on weather conditions. This paper presents a novel methodology for daily maximum temperature prediction, based on a Support Vector Regression approach. The paper is focused on different measuring stations in Europe, from which different meteorological variables have been obtained, including temperature, precipitation, relative…

 Highlights: ► This paper presents a SVMr approach to daily temperature prediction. ► Different measuring stations in Europe, with different meteorological variables are considered. ► Comparisons with alternative neural methods have shown the good performance of the proposed approach.