Abstract:
In this paper we present a methodology to perform water system optimization under climatic and hydrological uncertainty, in order to reach a sufficient degree of systems reliability to determine the risk of significant water deficiencies. Different generation techniques are compared to set up and analyze a number of scenarios. Uncertainty is modeled by a scenario-tree in a multistage environment, which includes different possible configurations of inflows in a wide time-horizon. The mathematical model structure representing the multiperiod optimization stochastic problem allows to handle a huge number of variables and constraints. The solutions of the optimization process on the scenario-tree are post-processed in order to reach a “robust” solution. The aim is to identify trends and essential features on which to base a robust decision policy
