Field test experiences with neural network models for short term electrical load forecasting in West Switzerland

Piras, A.Germond, A.Jaccard, Y.Buchenel, A.2007-04-042007-04-042007-04-041996https://infoscience.epfl.ch/handle/20.500.14299/4427In this paper, the authors present successful field test experience in the use of neural networks for short-term electrical load forecasting. After reviewing the importance of load forecasting as a key planning tool for a modern energy management system (EMS), they outline the advantages of using neural networks, how they are implemented, the choice of explicative variables and the selection of appropriate models. In the field test, a fully automatic load forecasting service was implemented. Numerical results are presented showing the importance of forecasted temperatures for a good load forecast and a comparison of rural and urban regions in terms of accuracyload forecastingload managementneural netspower system analysis computingpower system planningWest Switzerlandshort-term electrical load forecastingfield test experiencesneural network modelspower systemsforecasted temperaturesrural regionsurban regionsforecast accuracyField test experiences with neural network models for short term electrical load forecasting in West Switzerlandtext::journal::journal article::research article