Hydrothermal scheduling in Norway using stochastic dual dynamic programming; a large-scale case study

We test the stochastic dual dynamic programming (SDDP) approach on a system an order of magnitude larger than previously published studies. The analysis shows that the SDDP-approach can be applied to very large system sizes to solve the hydropower scheduling problem through formal optimisation and obtain individual decision variables for every reservoir. However, this can be very time-consuming compared to other existing models based on other principles. The results from our SDDP-based model compare favorably to an aggregation-disaggregation model which is in operational use in the power market when using statistical inflow series as input to the models.