Microgrids are a feasible path to deploy smart grids, an intelligent and highly automated power system. Their operation demands a dedicated communication infrastructure to manage, control and monitor the intermittent sources of energy and loads. Therefore, smart devices will be connected to support the growth of grid smartness increasing the dependency on communication networks, which consumes a high amount of power. In an energy-limited scenario, one of the main issues is to enhance the power supply time. Therefore, this paper proposes a hybrid methodology for microgrid energy management, integrated with a communication infrastructure to improve and to optimize islanded microgrid operation at maximum energy efficiency. The hybrid methodology applies some control management rules, such as intentional load shedding, priority load management, and communication energy saving. These energy saving rules establish a trade-off between increasing microgrid energy availability and communication system reliability. To achieve a compromised solution, a continuous time Markov chain model describes the impact of energy saving policies into system reliability. The proposed methodology is simulated and tested with the help of the modified IEEE 34 node test-system.

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Managing a wireless sensor network is not a trivial task. Due to its limitations, such as sensors equipped with low power batteries, it is essential to extend the lifetime of the network. This task becomes harder when dealing with heterogeneous wireless sensor networks, in which sensors have different physical characteristics, such as battery capacity and radio transmission range. This paper proposes a model to dynamically select a sensor allocation approach in order to choose a set of sensors to process an application request. This selection takes into account the application characteristics and the physical aspects of the sensors.

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