Title :
Forecasting the next day load profile using load profiling information and meteorological variables
Author :
Sousa, J.C. ; Jorge, Humberto M. ; Neves, Lucio P.
Author_Institution :
Dept. of Electr. Eng., Polytech. Inst. of Leiria, Leiria, Portugal
Abstract :
The article proposes a new approach to support the process of forecasting the hourly electric load values for the following day. The adopted methodology based on neural networks is only supported by detailed information related with consumers´ typical behavior and climatic information. The case study was tested in two real distribution substation outputs, demonstrating its effectiveness and practical applicability.
Keywords :
load forecasting; neural nets; power distribution; power engineering computing; substations; climatic information; consumer behavior; distribution substation outputs; hourly-electric load value forecasting; load profiling information; meteorological variables; neural networks; next-day load profile forecasting; Forecasting; Load forecasting; Load modeling; Low voltage; Neurons; Predictive models; Training; Load Forecasting; Load Profiling and Neural Networks;
Conference_Titel :
Energetics (IYCE), Proceedings of the 2011 3rd International Youth Conference on
Conference_Location :
Leiria
Print_ISBN :
978-1-4577-1494-8
