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Publicação
Short-term load forecasting using information obtained from low voltage load profiles
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| Recent researches in load forecasting are quite often based on the use of neural networks in order to predict a specific variable (maximum demand, active electric power or hourly consumption) using past values of the same variable and other exogenous factors proved to influence the value being predicted. This work aims to explore different input patterns in neural networks incorporating information derived from load profiles of different consumers' classes. | 189.99 KB | Adobe PDF |
Orientador(es)
Resumo(s)
Recent researches in load forecasting are quite often based on the use of neural networks in order to predict a specific variable (maximum demand, active electric power or hourly consumption) using past values of the same variable and other exogenous factors proved to influence the value being predicted. This work aims to explore different input patterns in neural networks incorporating information derived from load profiles of different consumers' classes.
Descrição
Article number 4915229, 2nd International Conference on Power Engineering, Energy and Electrical Drives, POWERENG 2009, 18 March 2009 through 20 March 2009 - Code 77128
Palavras-chave
Load forecasting Low voltage Neural networks Technology management Autocorrelation Weather forecasting Artificial neural networks Predictive models Computer networks Research and development
Contexto Educativo
Citação
J. M. C. Sousa, L. M. P. Neves and H. M. M. Jorge, "Short-term load forecasting using information obtained from low voltage load profiles," 2009 International Conference on Power Engineering, Energy and Electrical Drives, Lisbon, Portugal, 2009, pp. 655-660, doi: https://doi.org/10.1109/POWERENG.2009.4915229.
Editora
IEEE Canada
Licença CC
Sem licença CC