Time series forecasting: unified concepts and computer implementation
Time series forecasting: unified concepts and computer implementation
System identification: theory for the user
System identification: theory for the user
Time Series Analysis: Forecasting and Control
Time Series Analysis: Forecasting and Control
A meta-heuristic framework for forecasting household electricity consumption
Applied Soft Computing
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This paper examines the application of artificial neural networks (ANNs) to the modelling and forecasting of electricity demand experienced by an electricity supplier. The data used in the application examples relates to the national electricity demand in the Republic of Ireland, generously supplied by the Electricity Supply Board (ESB). The paper focusses on three different time scales of interest to power boards: yearly (up to fifteen years in advance), weekly (up to three years in advance) and hourly (up to 24 h ahead). Electricity demand exhibits considerably different characteristics on these different time scales, both in terms of the underlying autoregressive processes and the causal inputs appropriate to each time scale. Where possible, the ANN-based models draw on the applications experience gained with linear modelling techniques and in one particular case, manual forecasting methods.