An Edge Computing-Based Data Collection Method for Smart Grid Data Acquisition System

As an increasing number of data collection devices being integrated into the power system, the volume of data to be uploaded to the cloud is also growing annually. This data plays a crucial role in the continuous operation of the power system. However, the current method of information exchange through IoT management platforms results in a significant amount of redundant data when dealing with a massive number of collection devices. This severely limits the further widespread application of smart devices. To address this issue, this paper proposes a device information acquisition method based on edge computing. Devices are categorized and clustered according to their nature. Subsequently, data compression is achieved by comparing and consolidating identical data. The algorithm considers the timeliness of the clustering process and establishes conditions for re-clustering based on empirical design. Finally, we designed a device data collection system based on this algorithm, demonstrating its feasibility.