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 of ten 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.
Meteorological parameters influence for medium term load forecasting / Falvo, Maria Carmen; Lamedica, Regina; A., Prudenzi. - STAMPA. - (2006), pp. 1296-1301. (Intervento presentato al convegno IEEE/PES Transmission and Distribution Conference and Exposition tenutosi a Dallas, TX nel MAY 21-26, 2006) [10.1109/tdc.2006.1668698].
Meteorological parameters influence for medium term load forecasting
FALVO, Maria Carmen;LAMEDICA, Regina;
2006
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 of ten 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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
