Wind power day-ahead uncertainty management through stochastic unit commitment policies

Abstract

Day-ahead uncertainty management in power systems has traditionally been approached by means of multistage decision making and operating reserve requirements. An alternate approach for managing uncertainty is a stochastic formulation, which allows the explicit modeling of the sources of uncertainty. The large investments in wind power has increased the importance of operations uncertainty management due to the considerable operational uncertainty wind plants have. This paper evaluates the benefits of a combined approach that uses stochastic and reserve methods for the efficient management of uncertainty in the unit commitment problem for systems with significant amount of wind power. Numerical studies on a model of the PSCo system show that the unit commitment solutions obtained for the combined approach are robust and superior with respect to the traditional approach in terms of economic metrics and curtailed wind power.