Putting Sensor Data to the Service of the Smart Grid: From the Substation to the AMI
Abstract
One of the requirements of a smart grid (SG) is making the electrical network and its subsystems aware of their condition. The deployment of various sensing devices plays an essential part in achieving this goal. Nevertheless, data generated by this deployment needs to be well managed so that it can be leveraged for operational improvement. Data aggregation is perceived as an important technique for managing data in the SG in general, and in its Advanced Metering Infrastructure (AMI) in particular. Indeed, data aggregation techniques have been used in order to reduce communication overhead in SG networks. However, in order to fully take advantage of the aggregation process, some level of intelligence should be introduced at concentrator nodes to make the network more responsive to local conditions. Moreover, by using a more meaningful aggregation technique, entities can be accurately informed of any disturbance. This paper contributes an agent-based approach for data and energy management in an SG. It also proposes CoDA, a correlation-based data aggregation technique designed for the AMI. CoDA employs fuzzy logic to evaluate the correlation between several messages received from Smart Meters (SMs). Analysis and simulation results show the benefits of the proposed approach w.r.t. both packet concatenation and no aggregation approaches.