Effects of Wind Penetration in the Scheduling of a Hydro-Dominant Power System
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This talk presents a computational model that is able to determine the optimal economic generation scheduling considering decisions in a system with hydro, thermal and wind power plants. The algorithm is based on the class of sampling-based decomposition algorithms used to solve large-scale multi-stage stochastic optimization problems. A case study composed by several simulation runs of the model is presented and the results about wind power effects in the scheduling of power generators are discussed. The model and the solution strategy based on Stochastic Dual Dynamic Programming is implemented in Python and Pyomo.