Abstract
The problem of forecasting three-hour inflows and controlling a run-of-the-river hydroelectric plant is examined with respect to remotely controlled powerhouses of a hydroelectric system operated by Alcan Smelters and Chemicals Ltd. in the Province of Québec, Canada. Autoregressive-moving average (ARMA) models and transfer function-noise models are described and recent developments with respect to the identification, parameter estimation, and diagnostic checking stages of model construction are reviewed for both types of models. The three stages of model construction are applied to sample data and the most appropriate ARMA and transfer function-noise models are selected and discussed. The chosen transfer function-noise model relates flows at an upstream powerhouse and two tributaries to inflows at the downstream powerhouse. Flows from the tributaries are acquired via a GOES satellite. The selected model represents an important component of the control strategy for the downstream powerhouse.
Published Version
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