A Cluster Management System for Underwater Unmanned Energy Storage Stations Based on Edge-Cloud Integration Technology and AI Technology
Mengfei Xu, Yipeng Yang, Changqing Qiu · 2023
The underwater unmanned energy storage station has many special characters which caused communication limitations with the shore-based operation center that handles large amounts of data. It is necessary to design an independent on-site management system for the distributed underwater unmanned energy storage station maintenance system, which uses edge computing for real-time monitoring. Additionally, after the key data of stations were sent to shore-based operation center, the cloud computing technology and big data mining technology and AI (Artificial Intelligence) technology were used to predict and effectively schedule the operational status and trends of the energy storage stations, thereby improving the supply efficiency and operational life of the energy storage station cluster.