CARNEIRO, T. C.; http://lattes.cnpq.br/5343540612148877; CARNEIRO, Tatiane Carolyne.
Resumo:
This paper presente monthly operating rules based on Implicit Stochastic
Optimization (ISO) and Artificial Neural Networks (ANN) for a water systern
located in Paraíba's outback, Brazil. The ISO technique consists of optimizing the
system operation using a set of possible scenarios as input and, after, utilizing the
optimal outcomes in order to construct reservoir operating rules. In this study, ANN
were used for relating reservoir releases to inicial storage, current inflow, monthly
estimations of potencial evaporation and demand, and previous reservoir release.
The synthetic scenarios of reservoir inflows were generated by the Fragment
Method (FM). The results obtained by the MF indicate that this approach has
potential for simulating monthly flows in semiarid regions. The monthly operatirlg
tules obtained by the ISO-ANN modem were applied to the operation of Coremas -
Mãe d'Água reservoir and sustainability criteria were used for analyzing the
results. The outcomes suggest the ISO-ANN model is superior to the standard
tules of operation and similar to the application of a determinist modem with the
knowledge of inflows for the whole operating horizon. As a consequence, this
model may support the decision-making process for monthly operation of
reservoirs in semiarid regions.