E. M Constantinescu, V. M. Zavala, M. Rocklin, S. Lee, and M. Anitescu, "Unit Commitment with Wind Power Generation: Integrating Wind Forecast Uncertainty and Stochastic Programming," Technical Memorandum ANL/MCS-TM-309, September 2009. [pdf]
We present a computational framework for integrating of the state-of-the-art Weather Research and Forecasting (WRF) model in stochastic unit commitment/energy dispatch formulations that account for wind power uncertainty. We first enhance the WRF model with adjoint sensitivity analysis capabilities and a sampling technique implemented in a distributed-memory parallel computing architecture. We use these capabilities through an ensemble approach to model the uncertainty of the forecast errors. The wind power realizations are exploited through a closed-loop stochastic unit commitment/energy dispatch formulation. We discuss computational issues arising in the implementation of the framework. In addition, we validate the framework using real wind speed data obtained from a set of meteorological stations. We also build a simulated power system to demonstrate the developments.