Convex Hull Pricing As a Risk Mitigation Device in Unit Commitment

We use convex hull pricing to explicitly price the risk associated with uncertainty in large power systems scheduling problems. Uncertainty associated with renewable generation (e.g. solar and wind) is highlighting the need for changes in how power production is scheduled. However, there are two main challenges that need to be overcome. The first is computational time: provably near-optimal solutions to large optimization problems need to be found very quickly. Secondly, there is a need for a novel method to achieve a favorable equilibrium between the cost benefits of renewable energy generation and the potential financial ramifications arising from inaccurate predictions. We propose to use convex hull pricing to price the risk associated with uncertainty in production a priori. This results in a deterministic scheduling problem with a modified objective function that is similar to those currently solved in practice. Computational results show that we are able to capture most of the benefits of fully stochastic models without the additional computational cost.