Title :
Meteorological Parameters Influence for Medium Term Load Forecasting
Author :
Falvo, M.C. ; Lamedica, R. ; Prudenzi, A.
Author_Institution :
Dept. of Electr. Eng., Rome Univ.
Abstract :
The present paper reports a correction algorithm based on meteorological parameters, to apply to a medium-term load forecasting (MTLF) available system. To this aim a correlation study between various meteorological data and electric load of a Municipal Utility has been performed. In particular the analyzed meteorological data concern temperature and humidity gathered along a period often years. This correlation analysis made possible to heuristically identify the correction algorithm that is finally tested by evaluating forecasting accuracy of a MTLF system, based on a artificial neural network (ANN), using only electric time series
Keywords :
load forecasting; neural nets; power engineering computing; time series; Municipal Utility; artificial neural network; electric load; electric time series; forecasting accuracy evaluation; medium term load forecasting; meteorological data; Algorithm design and analysis; Artificial neural networks; Data analysis; Humidity; Load forecasting; Meteorology; System testing; Temperature; Time series analysis; Weather forecasting;
Conference_Titel :
Transmission and Distribution Conference and Exhibition, 2005/2006 IEEE PES
Conference_Location :
Dallas, TX
Print_ISBN :
0-7803-9194-2
DOI :
10.1109/TDC.2006.1668698
