A continuous-time hierarchical aggregation framework of dis-tributed energy resource

The high penetration of distributed energy resources brings problems including limited temporal granularity and computation burden. Thus, to coup with aforementioned issues, this paper provides a continuous-time hierarchical aggregation framework of distributed energy resource. First, the hierarchical system is modelled in a discrete-time manner. The model includes distributed energy resources cluster and virtual power plant. Then, the discrete-time model is equivalently transformed into the linear continuous-time model based on Bezier curve. Subsequently, the distributed energy resource clusters in virtual power plant are aggregated through Minkowski-sum. To overcome computational intractability, we approximate the Minkowski-sum using maximum-volume inner approximations, based on the optimization of affine transformations for a given high-dimensional convex polytope. Next, the aggregated distributed energy resource clusters, along with other individual distributed energy resources, are integrated into the aggregation of virtual power plant. Specifically, a min-max robust optimization with objective function as 0 is used to iteratively reveal the aggregated feasible flexibility region of virtual power plant. Also, to embed the proposed framework into real-world power system, the operation procedure and responsibilities of respective entities are explained. Finally, the proposed aggregation framework is verified on a hierarchical power system.