On the effectiveness of data aggregation to manage network congestion in smart grid AMI

摘要

The inclusion of various intelligent electronic devices such as smart meters for AMI is expected to result in intermittent or frequent network congestion in communication networks without additional network infrastructure investments. An approach to deal with such a data volume challenge in smart grids is to aggregate data streams within the network. This paper proposes a novel approach to manage AMI data traffic volume through data aggregation that estimates the expected network delays messages would suffer and dynamically determines an aggregation policy such that the electric utility gets the information in a more timely manner, albeit at a lower data granularity. The proposed algorithm is evaluated for different network congestion scenarios using the NS-3 simulator. The simulation results illustrate that the proposed algorithm is immensely effective in controlling the increase in network latencies as congestion levels increase in AMI networks. In addition, it does well in satisfying quality-of-service (QoS) requirements in terms of data granularity required by smart grid applications.