Title of article :
Searching for the electric load-weather temperature function by using the group method of data handling
Author/Authors :
Marino Sforna، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 1995
Abstract :
This paper reports on some results of a study regarding the electric power system of the Italian Power Company (ENEL) in which, when possible, an electric load-weather temperature link has been presented. In particular, the focus has been on the connection between maximum and minimum daily temperatures and the corresponding daily electric power and load. In order to underline the link between the variables, temperature and electric load, this study examines the entire national electric network and also considers more limited areas such as pluriregional and departmental networks. The methodology adopted, based on a particular regression method called the group method of data handling (GMDH), has been the subject of study because it is innovative for the power system world and has never been applied to such a problem before.
Keywords :
load forecasting , Data handling , Neural networks , Energy management
Journal title :
Electric Power Systems Research
Journal title :
Electric Power Systems Research