-

 

 

 




Optimization Online





 

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 )

Citation:

Download: [PDF]

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

Modify/Update this entry


  Visitors Authors More about us Links
  Subscribe, Unsubscribe
Digest Archive
Search, Browse the Repository

 

Submit
Update
Policies
Coordinator's Board
Classification Scheme
Credits
Give us feedback
Optimization Journals, Sites, Societies
Mathematical Programming Society