This paper presents a methodology to linguistically explain the optimal operation of a hydroelectric power plant. It consists on an optimal control approach in which a Neural Fuzzy Network works in parallel with a deterministic optimization model. The knowledge acquired by the network throughout the training phase is written as a set of fuzzy rules and the optimal operation can be interpreted by simple sentences of the type if < antecedent > then < consequent > . The results show that the network is able to learn the numerical decisions of the optimization model and can translate the numerical data into sentences that can be easily understood by human beings.
Hydroelectric power systems; intelligent control; optimization; fuzzy hybrid systems; linguistic support
