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As electric vehicles (EVs) proliferate and dominate the roads, public charging will be required extensively. Wide range coverage of energy information is required on fingertips for taking decisions at different levels and for all stakeholders. For this reason, a need arises for a correlated and all-inclusive framework that trades the unilateral discriminatory benefits with the combined benefit of all. At the heart of such frameworks lies communication technologies to support and manage energy transfer between vehicles and the power grid, known as the Internet of EVs. This paper adds two main contributions to the work presented in the literature on the subject matter. First, the communication requirements, standards, and protocols for applications involving this mobile prosumer management in the pre-connection stage to the electric grid are outlined. Second, and based on the aforementioned assessment, this paper proposes a decentralized hierarchical multiagent system that serves as a framework for real-time bilateral decision support for EVs and the power system. The effectiveness of the proposed framework and the credibility of using the communication middleware and means are experimentally verified on a group of connected vehicles communicating with a higher end server. Also, the seamless integration between the on-board and the higher end decision support systems is demonstrated in case studies. [ABSTRACT FROM AUTHOR]

This paper proposes a multiagent-based energy market for multimicrogrid systems using game-theoretic and hierarchical optimization approaches. The proposed method is tailored to achieve the optimal operation of smart microgrids in distribution systems. Because of rapid load variations in distribution systems, it is necessary to develop fast optimization algorithms which minimize the power mismatch in and among microgrids. In this paper, a three-level market framework is proposed. The first level comprises a game-theoretic double-auction mechanism for the day-ahead market while the next two levels are optimal rescheduling and intermicrogrid reverse auction model for the hour-ahead and real-time markets, respectively. Using the hierarchical optimization algorithm in a multiagent-based area, it is anticipated to not only minimize the optimization solution time, but also reduce the dependency on the network in grid-connected mode or load shedding in islanded mode. Using this approach, load demand response capabilities along with rescheduling of Distributed Energy Storage Systems and distributed generations could be utilized in all market levels, which will lead to optimal operation of multimicrogrid systems. Agents are developed in DIgSILENT PowerFactory and dynamic data exchange is activated for communication among agents communicating through a data distribution service which utilizes the real-time publish-subscribe communication protocol. The developed framework is applied to the modified 37-bus IEEE distribution test feeder system to validate the effectiveness of this market structure. [ABSTRACT FROM AUTHOR]