Towards ServiceOriented and Intelligent Microgrids The current energy transition implies fundamental changes in energy systems, in both their structure and operation. In this context, microgrids have the potential to reshape the traditional power grid, empowering the role of smallscale renewable power generators towards more sustainable, costeffective, and reliable energy systems. Microgrids are operated by energy management systems whose development is driven mainly by the contributions of technologies for distributed energy resources and techniques for optimal planning of loads. Yet, little attention is given to the design of such systems as software tools, whose capabilities are often limited because of a monolithic structure. We postulate that such systems need to intertwine both perspectives if microgrids are going to become a realised potential. We therefore propose a novel design of an energy management system that considers both perspectives and is based on the principles of serviceorientation. We implement the proposed design into a serviceoriented energy management system prototype and we run simulations with real data to test its feasibility.

RealTime Multiobjective Microgrid Power Management Using Distributed Optimization in an AgentBased Bargaining Framework In this paper, we propose a multiobjective power management procedure for microgrids (MGs). Through this procedure the power management problem is modeled as a bargaining game among different agents with different sets of objective functions. Nash bargaining solution (NBS) is employed to find the solution of the bargaining game. NBS lies on the Paretofront of the power management problem. Moreover, it introduces a unique and fair balance among the objective functions of different agents and removes the need to track the whole Paretofront in realtime. Distributed gradient algorithm is applied to find the NBS through a modular distributed decision framework without using a central control unit. In this way, the problem of data privacy of different parties within the MG is addressed. The proposed methodology has been tested through simulations on islanded and gridconnected MGs under different pricing scenarios (fixed versus timeofuse pricing).