Portfolio Optimization of Hydroelectric Assets Subject to Financial Indicators

The objective of this article is to present a benchmarking of financial indicators implemented in hydroelectric stochastic risk management models. We present three model formulations using a tree approach for hydroelectric optimization using three procedures for financial risk control: minimum revenues (Rmin), value-at-risk (VaR) and conditional VaR (CVaR). According to their properties and their formulation in each model we compare them theoretically based on two criteria: their adequacy for electricity portfolio optimization subject to risk constraints and the feasibility of their implementation inside the state of the art (SDDP) algorithm appropriate for large scale energy systems. Using numerical examples we verify the statements derived from the theoretical comparison.