Modeling and Solving a Large-scale Generation Expansion Planning Problem under Uncertainty
Energy Systems, 2011
In this paper, Professor David Woodruff and co-authors Shan Jin and Sarah Ryan from Iowa State University, and Jean-Paul Watson from Sandia National Laboratories formulate a generation expansion planning problem to determine the type and quantity of power plants to be constructed over each year of an extended planning horizon, considering uncertainty regarding future demand and fuel prices.
This model is expressed as a two-stage stochastic mixed-integer program, which the authors
use to compute solutions independently minimizing the expected cost and the Conditional
Value-at-Risk; i.e., the risk of significantly larger-than-expected operational