Model-based performance evaluation of large-scale smart metering architectures

Smart meter devices are used to monitor and control energy consumption and are interlinked with smart grids. Their growing use leads to an extensive amount of available data to be processed and causes smart grids to evolve to large-scale systems of systems. Guaranteeing appropriate scalability and performance characteristics is a tremendous challenge. In this paper, we focus on the provisioning of sufficient computing capacity to efficiently analyze the produced data in such a distributed system. For this purpose, we show the use of performance models to plan and simulate this distributed computation in smart grid systems. It demonstrates how different system architectures can be evaluated and required capacities can be estimated to cope with the occurring data volume. We analyze response times for time-critical tasks and assess the scalability of smart grid systems.