Author(s): T. Rocha; I. G. Hidalgo; A. F. Angelis; J. E. G. Lopes
Linked Author(s):
Keywords: No keywords
Abstract: The operation planning of hydropower plants depends on the inflow forecasting. Usually, the inflow forecasting is done from mathematical, stochastic or hydrological models. This paper presents the use of Soil Moisture Model Accounting Procedure (SMAP) to predict daily inflows into hydropower plants. SMAP is a deterministic model of hydrological simulation of the type rainfall-runoff transformation. Our objective is to evaluate the accuracy of its results in order to support the decisions of water storage and power generation of hydropower plants. Generalized Reduced Gradient algorithm for nonlinear optimization is employed. SMAP performance is analyzed through three indicators: Nash-Sutcliffe efficiency, percent bias, and ratio of the root mean square error to the standard deviation. The results show that SMAP is a good alternative to predict water inflows. We hope to contribute for the improvement of the power system planning, avoiding the thermal complementation and reducing the electricity cost.
Year: 2016