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A Computational Framework for Uncertainty Quantification and Stochastic Optimization in Unit Commitment With Wind Power Generation

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5 Author(s)
Constantinescu, E.M. ; Math. & Comput. Sci. Div., Argonne Nat. Lab., Argonne, IL, USA ; Zavala, V.M. ; Rocklin, M. ; Sangmin Lee
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We present a computational framework for integrating a state-of-the-art numerical weather prediction (NWP) model in stochastic unit commitment/economic dispatch formulations that account for wind power uncertainty. We first enhance the NWP model with an ensemble-based uncertainty quantification strategy implemented in a distributed-memory parallel computing architecture. We discuss computational issues arising in the implementation of the framework and validate the model using real wind-speed data obtained from a set of meteorological stations. We build a simulated power system to demonstrate the developments.

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Power Systems, IEEE Transactions on  (Volume:26 ,  Issue: 1 )