Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/11531/5549
Título : New variables to improve electricity and natural gas consumption forecasting: dynamic degree-days
Autor : Sánchez Ubeda, Eugenio Francisco
Berzosa Muñoz, Ana
Fecha de publicación : 7-nov-2011
Editorial : Universidad de La Laguna (ULL) y Asociación Española de Inteligencia Artificial (AEPIA) (Tenerife, España)
Resumen : 
This paper describes a new family of derived variables to measure the efect of outdoor air temperature in electricity and natural gas consumption. The proposed Dynamic Degree-Days (DDD) are temperature-derived functions allowing the definition and use of new quantitative indexes which can help to explain easily the daily variations of electricity and natural gas consumption due to temperature. The DDD are based on a piecewise-linear model for daily temperature, previously adjusted using historical data. These new degree-days allow improving energy forecasting models as well as better monitoring energy performance. Illustrative results are presented.
Descripción : Capítulos en libros
URI : http://hdl.handle.net/11531/5549
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