# Towards Optimality Preserving Aggregation for Scheduling Distributed Energy Resources

## TL;DR

This paper proposes a formal method for aggregating heterogeneous energy storage devices in power system scheduling, ensuring optimality is preserved despite model simplification, thus reducing computational complexity.

## Contribution

It introduces mild conditions on device constraints that guarantee aggregation does not compromise optimal scheduling solutions.

## Key findings

- Aggregation preserves optimality under specified conditions.
- The method reduces computational burden in scheduling heterogeneous energy resources.
- Discussion of limitations and potential extensions provided.

## Abstract

Scheduling the power exchange between a population of heterogeneous distributed energy resources and the corresponding upper-level system is an important control problem in power systems. A key challenge is the large number of (partially uncertain) parameters and decision 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 alleviate these issues. However, despite the frequent use of aggregation for storage, few works in the literature provide formal justification. In the present paper, 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 conclude with a discussion of limitations and possible extensions of our findings.