A Projection Method for Aggregating Large-Scale DERs with Heterogeneity

Abstract

The power consumption flexibility of distributed energy resources (DERs) must be aggregated to enable effective interaction with power systems. However, model heterogeneity, geographical dispersion, and the large number pose significant challenges to aggregation. This paper first models DER flexibility by explicitly incorporating heterogeneity in both state variables and available time periods, represented through polytopes of heterogeneous dimensions. The aggregation of DERs is then formulated as a standard projection maximal inner approximation (MIA) problem. To efficiently and accurately solve this problem, a novel linear programming (LP)-based algorithm is developed. Furthermore, a hierarchical framework is introduced to enable large-scale aggregation, within which a Minkowski-closed family is proven, allowing accurate and efficient secondary aggregation through vector addition. In addition, generalized operating envelopes (OEs) are proposed for distribution system operators (DSOs) to establish and communicate network constraints, enabling integration into the aggregation process without disclosing sensitive network information. Numerical experiments validate the proposed formulations and demonstrate superior accuracy and scalability of the proposed method while maintaining high computational efficiency.