Energy Scheduling of a Technical Virtual Power Plant in Presence of Electric Vehicles

In modern power systems, technical virtual power plants (TVPPs) play an important role enabling presence of distributed energy resources (DERs) in electricity markets. In this paper, strategy of using the available energy resources for a TVPP is put under investigation. A new optimization framework is presented for problem of TVPP energy scheduling by taking operational constraints of distribution network into account. In the proposed model, photovoltaic (PV) units and micro turbines along with the electric vehicles (EVs) are scheduled in such a way that the profit of TVPP owner would be maximized. The uncertainty in output generation of PV units is modeled by adopting fuzzy c-means (FCM) clustering algorithm. Also, the predicted amount of the load of TVPP is included in the scheduling problem using scenario-based approach. The model is mathematically formulated in the format of mixed integer linear programming which guarantees obtaining the global optimum solution. The capability of the model is examined through its implementation on the IEEE RBTS-Bus5 distribution test system. The obtained results demonstrate the applicability and effectiveness of the proposed model.