Approximating Hydropower Systems By Feasibility Spaces In Stochastic Dual Dynamic Programming

This work investigates and improves methodology for approximating hydropower systems by feasibility spaces, which can be embedded in the stochastic dual dynamic programming algorithm and applied in the context long-term hydrothermal scheduling. The feasibility spaces are derived from optimization of the detailed hydropower system and are expressed in few dimensions to facilitate efficient computations. Test results from a case study for the Norwegian power system demonstrate how feasibility spaces serve to realistically constrain the hydropower system.