Industry-academia partnership for the design and i.. (SMART-NRG)
Industry-academia partnership for the design and implementation of an efficient, reliable and secure smart energy network
Start date: Jan 1, 2014,
End date: Dec 31, 2017
Smart energy networks (SENs) are electric systems that use two-way networking technologies, cyber-secure communications technologies, and computational intelligence and control in an integrated fashion to efficiently manage energy consumption with the aim of providing a new electricity grid that is clean, safe, secure, reliable, resilient, efficient, and environmentally sustainable. SENs can be well regarded as a system of many systems, whose design challenges, requirements, and expectations can only be achieved through a holistic analysis, design, and optimization of all its components. In SMART-NRG, we will go beyond state-of-the-art approaches for SENs by introducing an innovative and integrated protocol stack, which will be made of three interlinked and optimized sub-systems: i) reliable communications and networking; ii) smart energy management; and iii) security and protection, which are one-to-one connected to the three key functionalities of SENs. The sub-systems will be studied, optimized, and integrated in a very efficient protocol stack, which will be tested via system level simulations and hardware testbeds, and, eventually, will be integrated into commercial devices. According to this view, the project has four main scientific objectives:1. The proposal of a new protocol stack and network architecture for SENs integrating communications, energy management, and security protocols, along with their analysis, design, and optimization for smart metering applications.2. The analysis, the design, and the optimization of an efficient and reliable two-way smart meter communication infrastructure by embracing a stochastic network modeling framework.3. The analysis, the design, and the optimization of advanced smart energy management algorithms for better energy utilization.4. The analysis, the design, and the optimization of advanced security and privacy mechanisms for large-scale networks with reduced management and control overhead.
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