Adaptive Real-Time Convergence Estimation for Enhancing Reliability of Time Synchronization in Distributed Energy Monitoring System

In distributed energy monitoring systems, precise time synchronization is paramount for efficient data acquisition and energy management. With the high penetration of new energy sources, the distributed energy monitoring system will evolve into a complex heterogeneous network utilizing various short-range wireless communication technologies. Therefore, wireless communication-based time synchronization technologies will be widely applied, and it is important for the distributed energy monitoring system to be aware of the current time synchronization errors as this is crucial for accurate data processing. Our findings propose the first real-time convergence estimation method using an adaptive real-time convergence estimation (ARCE) algorithm, which can accurately estimate the current network time synchronization error and convergence status in real time. This ARCE algorithm is based on synchronization error and distribution of both synchronous and asynchronous time synchronization algorithm. The actual distributions of synchronization error are analyzed and evaluated using a significant amount of experimental results. According to the experimental results and simulations, ARCE can effectively detect the convergence state for all the comparisons. Therefore, ARCE can be used to evaluate the reliability of timestamps in data acquisition. Moreover, it can be utilized to enhance the adaptive capability of time synchronization algorithms, which could be robust and scalable for a large-scale and randomly deployed wireless networks.