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An Intelligent Approach for Medium Term Hydropower Scheduling Using Ensemble Model

  • Thais Gama de Siqueira
  • Ricardo Menezes Salgado
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 99)

Abstract

The medium term hydropower scheduling (MTHS) problem involves an attempt to determine, for each time stage of the planning period, the amount of generation at each hydro plant which will maximize the expected future benefits throughout the planning period, while respecting plant operational constraints. Besides, it is important to emphasize that this decision-making has been done based mainly on inflow earliness knowledge. To perform the forecast of a determinate basin, it is possible to use some intelligent computational approaches. In this paper one considers the Dynamic Programming (DP) with the inflows given by their average values, thus turning the problem into a deterministic one which the solution can be obtained by deterministic DP (DDP). The performance of the DDP technique in the MTHS problem was assessed by simulation using the ensemble prediction models. Features and sensitivities of these models are discussed.

Keywords

Medium Term Hydropower Scheduling Dynamic Programming Inflow Forecast Artificial Intelligence Predictive Models Ensembles 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Thais Gama de Siqueira
    • 1
  • Ricardo Menezes Salgado
    • 2
  1. 1.Institute of Science and TechnologyUniversity of AlfenasPoços de CaldasBrazil
  2. 2.Institute of Exact SciencesFederal University of AlfenasAlfenasBrazil

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