Stochastic optimisation of Hydro-Quebec hydropower installations: a statistical comparison between SDP and SSDP methods.

This paper examines the problem of finding an optimal operating policy for Hydro-Quebec's Manicouagan River and Outardes River hydroelectric installations. The solution method is based on the sampling dynamic programming (SSDP) algorithm. We use a new hydrologic state variable to capture the inflows regime, and this variable is given by a linear combination of the snow water equivalent and soil moisture. In real-time operation, this variable is calculated by a hydrologic model and incorporated in the operating policy to calculate the water released at each power plant. The algorithm is compared to the lag-1 stochastic dynamic programming (SDP) already implemented at Hydro-Québec, through a statistical analysis with a set of 40 synthetic historical inflow scenarios obtained by hydrologic modeling, using synthetic temperature and precipitation produced by a stochastic weather generator. The results of the analysis show that the SSDP operating policy is statistically superior to the operating policy of the lag-1 SDP model. The SSDP operating policy does not underestimate the volume of runoff occurring during the spring season contrary to SDP. Consequently, there is a reduction in the hm3 of water spilled, while the average annual generation is increased. [ABSTRACT FROM AUTHOR]