Transforming the electric power system to incorporating a considerably increased share of renewable distributed generation implicates new challenges for the control of the system. To overcome the known shortcomings of centralized control, e.g. regarding scalability and robustness, a decentralized, self-organized system of agents for generators, loads and storages is widely discussed. We focus on a dynamic aggregation of these units to participate on current and future energy markets for both active power and new ancillary services products. With these units participating in system services, rescheduling of units within clusters becomes a more complex task that should reflect grid usage properties. In this work, we develop grid related cluster schedule resemblance as a metric to analyze the grid usage changes using graph theory. This metric can be used to compare different rescheduling options regarding grid usage for both dynamic clusters of distributed energy resources and for rescheduling of static clusters like virtual power plants. An example is used to show that this metric can be used as a separate optimization target for the multi-criteria optimization problem of cluster rescheduling.
5 / 2013
Forschungsverbund Intelligente Netze Norddeutschland