A linear regression-based study for temperature sensitivity analysis of Iran electrical load

• Published in: 2008 IEEE International Conference on Industrial Technology pp. 1 - 7
• Main Authors: Moghaddas-Tafreshi, S.M., Farhadi, Mahdi
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-04-2008
• Subjects: Cooling; Correlation; linear regression; Load forecasting; Load modeling; Meteorology; neural networks; similar days; Temperature; Temperature sensors
• ISBN: 1424417058; 9781424417056
• DOI: 10.1109/ICIT.2008.4608590

In this paper sensibility of Iran network load to the temperature has been studied by the linear regression method. The linear regression analysis of Iranpsilas electrical load recognizes that the load pattern is heavily dependent on temperature, and finds a linear function between the load and the networkpsilas temperature. This study shows that temperature has a great effect on Iranpsilas network load, so that daily electrical load of Iran is function of the minimum, average and maximum temperatures of the forecasted day and the day before forecasted day too. Finally this paper shows that suitable input variables which can consider the temperature effect on Iran forecasted load in the short term load forecast (STLF) model are minimum, average and maximum temperatures of the forecasted day and the day before forecasted day. This analysis can be extended to all of the other environmental factors such as humidity, wind velocity and weather overlay too. Also this study can be performed for the other entire countries electrical network. It is worthy to say, the thermal model which has been designed based on this study has been tested in extended STLF softwares of Iran and their relative papers which have been written by the authors , have been accepted in some of the other international conferences.