Data aggregation using temporal and spatial correlations in advanced metering infrastructure

In this paper, we propose a data aggregation mechanism using temporal and spatial correlations in Advanced Metering Infrastructure of smart grid environment. Data aggregation is a process to collect the same type of data and transmit the aggregation data using predetermined function - sum, avg, min, etc. It decreases the transmission number and thus enhances energy efficiency. Each smart meter determines the transfer of new power usage data for reduction of transmission amount of data. When the difference of new data and previous data is less than the specified threshold, it is suppressed (temporal correlation). After clustering of geographically adjacent smart meters, each smart meter calculates the sum with the transmitted value of neighboring nodes within clustering and a node transmits own difference value including the sum (spatial correlation). We use the real power usage data during the most power-intensive week for the performance evaluation of our mechanism. The simulation results show that our approach reduces the transmission amount and energy consumption. We verify the accuracy of transmitted data using temporal and spatial correlation mechanism. Moreover, our approach provides minimal exposure of real power usage data without additional security method.