Short-term demand forecasting for real-time operational control of the Barcelona water transport network

Control and Automation(2014)

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摘要
This paper focuses on the forecast of the hourly water demand data of distinct pressure floors of the Barcelona water transport network. Several methods to forecast the hourly water demand are studied and compared with the aim of being applied for the operational control of the Barcelona 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. The paper focuses on the daily and hourly forecasts. In the hourly forecast, the exponential smoothing method is the most accurate. On the hand, the seasonal ARIMA and the exponential smoothing are similar in the daily time scale.
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关键词
demand forecasting,smoothing methods,water supply,barcelona water transport network,exponential smoothing method,hourly water demand data,real-time operational control,seasonal arima,short-term demand forecasting,structural models
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