Towards Optimality Preserving Aggregation for Scheduling Distributed Energy Resources

Scheduling the power exchange between a population of heterogeneous distributed energy resources and the corresponding upper level grid is an important control problem in power systems. A key challenge is the large number of (partially uncertain) variables that increase the computational burden and that complicate the structured consideration of uncertainties. Reducing the number of decision variables by means of aggregation can help alleviate these issues. However, despite the frequent use of aggregation for populations of storage devices, few works in the literature provide formal justification. In this article, we investigate aggregation of heterogeneous (storage) devices with time-varying power and energy constraints. In particular, we propose mild conditions on the constraints of each device, guaranteeing the applicability of an aggregated model in scheduling without any loss of optimality in comparison to the complete problem. We illustrate our findings on an relevant example.