Orateur
Description
The increasing penetration of wind and solar generation amplifies the uncertainty in the short term unit commitment problem for hydrothermal power systems, challenging, for example, schedules that are given by deterministic approaches, as is the case of the day ahead-unit commitment model (DESSEM) used for the official dispatch and price setting of the Brazilian system, over a seven day horizon. Such model employs a mixed integer linear programming approach (MILP), with some ad-hoc accelerating techniques. In this work a combined Branch and cut/ two stage Benders decomposition approach is proposed to consider uncertainties in that model, while trying to minimize deviations to the standard deterministic plan. The second stage subproblems capture the deviations in the scheduling of the first day, through a compact scenario set for renewable generation. The subproblem for each scenario is solved as a linear program with recourse, whose dual information generates Benders optimality cuts that are inserted “on the fly” as lazy constraints during the master Branch and Bound search, in a scheme labeled as “Branch and Benders Cut”. Preliminary tests on a simplified representative instance indicate that the stochastic layer introduces only a moderate computational burden while yielding a more reliable treatment of uncertainty and, consequently, smoother and more realistic energy price signals. Therefore, the formulation offers a practical and economically pathway for incorporating renewable variability and uncertainty into an industrial software for hydrothermal unit commitment, without causing a disruptive change in existing operational workflows for running the model by the Brazilian institutions.
Keywords: two stage stochastic programming; Branch and Benders Cut; hydrothermal unit commitment; renewable uncertainty; energy price formation.
