An Updated Survey Of Algorithmic Approaches To Unit Commitment Problems Under Uncertainty

The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program.

Unit Commitment problems under uncertainty are the basis of the hierarchy of models in plan4res case studies.

This paper provides a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. It starts with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. It then presents and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty.


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