Tuesday, 14:15 - 14:40 h, Room: MA 550


Michel Gendreau
Midterm hydro generation scheduling under inflow uncertainty using the progressive hedging algorithm

Coauthors: Fabian Bastin, Pierre-Luc Carpentier


Hydro-Québec, one of the largest electric utilities in North America, generates virtually all of its power supply using hydro plants. A key problem faced by planners is the midterm generation scheduling problem (MGSP), solved on a weekly basis, in which generation targets must be set for controllable hydro plants in order to manage reservoir energy storage efficiently over the coming months.
Reservoir inflows are the main source of uncertainty to account for in the decision-making process. In this paper, we model reservoir inflow uncertainty through scenario trees. We tackle the MGSP using the progressive hedging algorithm (PHA) (Rockafellar and Wets 1991). In our model, hydroelectric generation is given by concave piecewise-linear functions of the upstream reservoir storage and of water release. A key feature of our implementation of the PHA is a new penalty parameter update formula.
We assess our model and algorithm on Hydro-Québec’s power system (21 large reservoirs and 25 hydro plants) over a 93-week planning horizon with several load levels. Reservoir inflow uncertainty is modeled by a 16-scenario tree. Computational results show that the proposed approach is promising.


Talk 3 of the invited session Tue.2.MA 550
"Stochastic programming models for electricity generation planning" [...]
Cluster 18
"Optimization in energy systems" [...]


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