Tight Formulations for Unit Commitment with Different Levels of Details -- Part I: Models and Theoretical Insights
For power system operators, this work provides a theoretical foundation for selecting tight formulations that improve computational performance without sacrificing model fidelity.
The paper defines unit commitment models with different levels of detail and presents tight formulations based on the convex hull, including new proofs for ramping and start-up/shut-down constraints, to reduce computational burden in large-scale problems.
The unit commitment (UC) problem is paramount for optimal operation of power systems, but it faces computational limitations in large-scale settings, especially in investment or stochastic models, because of the binary variables that it contains. A lot of research has attempted to improve the computational performance of UC models, either by reducing model size, resulting in lower fidelity and accuracy, or by improving the tightness of the formulation. Tightness and model size are the best a priori indicators of the computational performance of UC models, but there is no clear overview of what the best formulation is for different generators. In this research, we define models with different levels of detail, and present a formulation for each level that is based on the convex hull. We show new proofs on the tightness of well-known formulations for ramping, and for start-up and shut-down costs and capabilities. These models, with a different level of detail, can be incorporated into large-scale problems to reduce the computational burden, as demonstrated in Part II.