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Type: Artigo
Title: Management of inflow forecasting studies
Author: Hidalgo, I. G.
Barbosa, P. S. F.
Francato, A. L.
Luna, I.
Correia, P. B.
Pedro, P. S. M.
Abstract: In hydroelectric systems, water inflow is important to coordinate a cascade and define the energy price. This paper presents a method for managing inflow forecasting studies with a specific module for advanced assessment. The main goal is to provide a structure that facilitates the analysis of water inflow prediction models. A case study has been applied to five mathematical models based on linear regression, artificial neural networks, and hydrologic simulation. These models present daily and monthly inflow forecasts for a set of hydroelectric plants and monitoring stations. The benefits of the proposed method are analyzed in four situations: water inflow prediction, performance evaluation of a specific model, research tool for inflow forecasting, and comparison tool for distinct models. The results show that implementation of the proposed method provides a useful tool for managing inflow forecasting studies and analyzing models. Therefore, it can assist researchers and engineering professionals alike by improving the quality of water inflow predictions
Subject: Usinas hidrelétricas
Sistemas de suporte de decisão
Country: Reino Unido
Editor: I W A
Rights: Fechado
Identifier DOI: 10.2166/wpt.2015.050
Date Issue: 2015
Appears in Collections:FEC - Artigos e Outros Documentos
FT - Artigos e Outros Documentos
FEM - Artigos e Outros Documentos

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