IoT and Edge Computing Based Direct Load Control for Fast Adaptive Frequency Regulation

Fast and accurate load control is helpful in maintaining grid frequency stability in case of emergency. Conventional under-frequency load shedding schemes (UFLS) suffer from low granularity while individual frequency-load control methods require sophisticated controllers and therefore are cost-prohibitive. This paper presents an innovative framework, Grid Sense, for fast and adaptive load control based on the Internet of Things (IoT), edge computing, and nonintrusive load monitoring (NILM). Grid Sense provides a promising cost-effective solution for large-scale deployment of individual load control using existing communication infrastructure in a distributed manner. Now that the Grid Sense system is being implemented in several pilot projects in State Grid Jiangsu Electric Power Company, this papers summarizes the major technologies utilized, system design considerations, and experimental results during its development process.