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

E.M. Constantinescu (emconsta***at***mcs.anl.gov)
V.M. Zavala (vzavala***at***mcs.anl.gov)
M. Rocklin (rocklin***at***mcs.anl.gov)
S. Lee (sangmin***at***cims.nyu.edu)
M. Anitescu (anitescu***at***mcs.anl.gov)

Abstract: We present a computational framework for integrating a state-of-the-art numerical weather prediction (NWP) model in stochastic unit commitment/energy 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 using real wind speed data obtained from a set of meteorological stations. Finally, we build a simulated power system to demonstrate the developments.

Keywords: weather forecasting, wind, unit commitment, energy

Category 1: Stochastic Programming

Category 2: Applications -- Science and Engineering (Control Applications )

Category 3: Applications -- OR and Management Sciences (Scheduling )


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Entry Submitted: 10/16/2009
Entry Accepted: 10/16/2009
Entry Last Modified: 03/05/2010

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