Electric Vehicles (EVs) are expected to dominate the transportation sector in the near future. To this end, intelligent real-time applications need to be employed. These applications aim not only to optimally manage the electric load of EVs and minimize operational costs but also to provide ancillary services to the grid, such as peak shaving and demand response. Vehicle-to-Grid (V2G) services, combined with the utilization of Renewable Energy Sources (RES), play a crucial role in the establishment of the 'Smart Grid'. The primary objective of this paper is to propose an innovative operation scheduling and control method for spatially distributed large-scale prosumers of Plug-in Electric Vehicles (PEVs) and RES. This approach considers these entities as a unified single entity and ensures the satisfaction of all constraints within the local networks. In pursuit of this goal, the concept of the 'Virtual Prosumer' is introduced. The Virtual Prosumer (VP) represents several distributed clusters of EVs and RES, such as Photovoltaic Parks and Wind Parks, located in different areas of the power system. However, from the perspective of the system operator, it is viewed as a single dispatchable prosumer. The proposed method focuses on three main aspects: 1) Real-time optimization of three distinct entities: VP, Cluster Electric Vehicles (CEVs), and PEVs. 2) Fulfillment of participants' constraints. 3) Management of numerous CEVs spotted in various geographical locations and connected to the same or different power networks. Field testing across multiple locations in Greece involved detailed simulations of large-scale Cluster Electric Vehicle (CEV) deployment. The results verify the applicability of our approach in effectively managing PEVs within the Virtual Prosumer framework. Notably, the proposed method reduces the charging cost by 11% compared to conventional charging. Furthermore, the maximum anticipated calculation time is significantly less than the time interval required for updating the set-points of PEVs and CEVs. This alignment with real-time requirements demonstrates the high reliability of Multi-Agent Systems (MAS) in addressing complex challenges. The proposed approach's versatility, scalability, and adaptability enable it to make significant contributions across a variety of industries and contexts. The investigation of the proposed methodology's potential and limitations for managing PEVs and RES within a VP framework underscores the necessity for comprehensive evaluations across varied economic and renewable resource scenarios. Future studies might concentrate on integrating the Internet of Energy (IoE) and implementing real-time Peer-to-Peer (P2P) energy transactions among participating agents, enhancing the capabilities of the proposed method and optimizing future energy systems.
