A reliable, secure, and energy efficient smart grid node allocation algorithm for heterogeneous network scenarios. (30th August 2018) - Kouhdaragh, Vahid; Tarchi, Daniele; Vanelli‐Coralli, Alessandro
Summary: The legacy power grid was becoming inefficient in the last decades, mostly due to a changed behavior in energy consumption and generation. To this aim, a novel approach, called smart grid (SG), has been introduced, enabling a smarter management of the electrical power grid, mostly based on a more efficient monitoring and management of the energy consumption and generation by exploiting the presence of sensing and actuator nodes. To properly work, the SG nodes need to interact among themselves and with the centralized monitoring system; therefore, an integrated SG communication network (SGCN) should be considered in the design. In this paper, wireless communication technologies have been considered for the SGCN due to their advantages with respect to wired connections, by focusing on heterogeneous networks (HetNets). However, because of radio resource shortage, an optimization process for their deployment should be considered. We resort in the following to a cost functions approach for optimizing the allocation of the SG node types to different Radio Access Technologies by considering both communication and energy aspects. The numerical results highlight that, thanks to the proposed allocation approach, it is possible to implement an efficient HetNet for supporting different SG node types by trading off between communication requirements and energy consumption. Abstract : The conventional power grid is becoming inefficient, mostly due to the changes in energy consumption and generation paradigms, leading to the introduction of a novel approach called smart grid. To work efficiently, the smart grid nodes needs to interact among them through a communication network able to satisfy their requirements. In this paper, a cost function‐based optimization technique for a heterogeneous wireless network is proposed, able to optimize the node allocation to the different radio networks.