Abstract
To increase the share of distributed energy resources (DER), they need to provide grid supporting ancillary services. In order to fulfill large energy products, virtual power plants (VPP) aggregate many small DER. In this paper we present an agent-based approach to the optimization problem of scheduling the DER of a VPP. We compare our approach which uses a evolutionary algorithm to one that uses a mathematical solver. When comparing the two approaches we found that our approach approximates the optimal solution well. The central benefit of our approach is that it scales better wrt. the VPP size. The increased scalability opens the ancillary services market to VPPs that aggregate more and smaller DERs.
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