Performance analysis of data processing architectures for the Smart Grid

Information and communication technology infrastructures play an important role to realize the full potential of Smart Grid (SG) applications. Several architectures proposed in the literature usually focus on communication requirement or data storage. However, it is still not clear which architecture best satisfies energy, storage, processing and communication requirements. The lack of understanding of key parameters, such as energy required, communication bandwidth, storage space, processing power, etc., has hindered the large scale SG deployments. In this paper, we investigate different data processing architectures for hierarchical power distribution networks. We introduce several key cost indicators to analyze hierarchical data processing architectures for the SG. In our evaluation, we consider realistic deployments in both dense and sparse environments and provide a detailed performance analysis of the proposed architectures. The results reported here are significant for SG designers, who can use them to discern the architecture that best fits the system requirements.