Integrating Uncertain Renewables in Power Systems: Leveraging Flexibility in Operational Models
C. Lindsay Anderson (BEE, Cornell)

The steady increase of electricity demand and the use of uncertain renewable energy sources requires improvement in the ability of power systems to adapt to changes in supply and demand. The first step in this evolution is the adaptation of planning and operational models to account for uncertainty on both the demand and supply side of the system. An additional challenge is the fact that power systems are very complex systems, with uncertainties that do not fit nicely into distributional paradigms. In this presentation a data-driven stochastic optimization model will be presented that uses a chance-constrained formulation to manage uncertainty in a manner that is customizable and scalable. Preliminary results will explore potential scalability and compare the chance-constrained approach with robust methods.