Adjustable Robust long-term energy planning under hydrological uncertainty

This work presents the Adjustable Robust Hidrothermal Coordination (ARHTC) methodology for handling hidrological uncertainty in long-term energy planning studies. Hydrological uncertainty is modeled via ellipsoidal uncertainty sets that are constructed using the sample mean and the sample covariance matrix of historical inflows of the Colombian hydro system. Rather than creating scenarios product of data sampling, the random inflows were allowed to be a continuous random variable via uncertainty sets. Thermal and hydro-power generation decisions are made as long as more hydrological information is released in order to guarantee adjustability to the current conditions. This methodology is computationally tractable and was implemented over a typical Colombian hydro chain. Results show that significantly higher robustness levels can be achieved with the help of affine decision rules compared to a static robust optimization methodology.