Abstract
This chapter deals with forecasting of hourly water demand data of different sectors of a WTN using the data obtained by their flowmeters. Several methods to forecast the hourly water demand are studied and compared with the aim of being applied for the operational control of any water transport network. The short-term forecast of the intraday series has a main feature: the double periodicity (daily and hourly). To address this issue, several extensions of the classical time series forecasting methods are proposed: seasonal ARIMA, structural models and the exponential methods without external information. This chapter focuses on the daily and hourly forecasts applied to the Barcelona transport water network. In the hourly forecast, the exponential smoothing method is the most accurate. On the other hand, the seasonal ARIMA and the exponential smoothing are similar in the daily timescale.
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Saludes, J., Quevedo, J., Puig, V. (2017). Demand Forecasting for Real-Time Operational Control. In: Puig, V., Ocampo-Martínez, C., Pérez, R., Cembrano, G., Quevedo, J., Escobet, T. (eds) Real-time Monitoring and Operational Control of Drinking-Water Systems. Advances in Industrial Control. Springer, Cham. https://doi.org/10.1007/978-3-319-50751-4_6
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DOI: https://doi.org/10.1007/978-3-319-50751-4_6
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