On Aggregation Performance in Privacy Conscious Hierarchical Flexibility Coordination Schemes

TL;DR

This paper introduces a method to quantify the performance of privacy-preserving hierarchical flexibility aggregation, focusing on energy storage systems, and highlights the impact of system parameters and demand profiles on aggregation accuracy.

Contribution

The paper presents a novel performance quantification framework for hierarchical flexibility coordination, emphasizing privacy preservation and the role of energy storage parameters.

Findings

Aggregation error is influenced by the power-to-energy ratio of ESS.

Grouping FPUs by similar power-to-energy ratios improves coordination performance.

Considering multiple demand timeseries is crucial for accurate aggregation error assessment.

Abstract

In this paper we introduce a method for performance quantification of flexibility aggregation in flexibility coordination schemes (FCS), with a focus on privacy preserving hierarchical FCS. The quantification is based on two performance metrics: The aggregation error and the aggregation efficiency. We present the simulation framework and the modelling of one complex type of flexibility providing units (FPUs), namely energy storage systems (ESS). ESS cause intertemporal constraints for flexibility coordination that lead to aggregation errors in case flexibility is aggregated from heterogeneous groups of FPUs. We identify one parameter responsible for the aggregation error to be the power-to-energy ratio of the ESS. A grouping of FPUs using similarity in their power-to-energy ratios is shown to improve the coordination performance. Additionally, we describe the influence of flexibility demand timeseries on the aggregation error, concluding that future assessments of aggregation errors should consider multiple representative demand timeseries, which is a non-trivial task. Finally, we discuss the applicability of the developed method to scenarios of larger system size.