**Modelling of Distributed Resource Aggregation for the Provision of Ancillary Services**

#### **Adam Lesniak \*, Dawid Chudy and Rafal Dzikowski**

Institute of Electrical Power Engineering, Lodz University of Technology, Stefanowskiego Str. 18/22, PL 90-924 Lodz, Poland; dawid.chudy@dokt.p.lodz.pl (D.C.); rafal.dzikowski@dokt.p.lodz.pl (R.D.)

**\*** Correspondence: adam.lesniak@dokt.p.lodz.pl; Tel.: +48-501-699-454

Received: 26 July 2020; Accepted: 1 September 2020; Published: 4 September 2020

**Abstract:** Nowadays, ancillary services (ASs) are usually provided by large power generating units located in transmission networks, while smaller assets connected to distribution systems remain passive. It is expected that active distribution systems will start to play an important role due to numerous issues related to power system operation caused mainly by developing renewable generation and restrictions imposed on conventional power generating units by climate policies. The future development of the power system managemen<sup>t</sup> will also lead to the establishment of new market agents such as distributed resource aggregators (DRAs). The article presents the concept of the DRA as part of an active distribution system enabling small resources to participate in wholesale markets, provide ASs and indicates the functions of the DRA coordinator in the modern power system. The proposed method of the DRA structure modelling with the use of the mixed-integer linear programming (MILP) is aimed at evaluating the optimal operation pattern of participating resources, the desired shape of the load profile at the point of common coupling (PCC) and the AS provision. The performed simulations of the DRA's operation show that various types of aggregated resources located in distribution networks are able to provide different services effectively to support the power system in terms of load–generation balancing and allow for further development of renewables.

**Keywords:** aggregation; ancillary services; distributed energy resources; optimization; power system operation
