Optimization of Reservoir Operation using Dynamic Programming and Fuzzy Neural Network

摘要

The reservoir optimization problem is a complex one due to stochastic nature of the hydrological events and the interplay of various conflicting objectives. Various models to derive operating policies to help the field engineers in operation of reservoir system exist. But a need for further refinement of the model is always there. The present work demonstrates a new approach using Fuzzy neural network for deriving the reservoir operating policies for a reservoir system. The Dynamic Programming - Fuzzy Neural Network (DPFN) model is applied to derive operating policies for Aliyar reservoir in Tamil Nadu, India. The proposed DPFN model using back propagation algorithm shows that the neural networks are capable of adapting their complexity to greater extent to match changes in the flow history and the model developed are more complicated.