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SGIT Achieves Breakthrough in Intelligent Early-Warning Technology for Large-Scale Energy Storage Power Stations

December 26, 2025 at 18:56 PM EST

ⓘ This article is third-party content and does not represent the views of this site. We make no guarantees regarding its accuracy or completeness.

Recently, the Intelligent Early-Warning Device for Operating Conditions of Large-Scale Energy Storage Power Stations based on Cloud-Edge Collaboration, independently developed by the State Grid Information & Telecommunication Group Co., Ltd. (SGIT), was successfully selected as a First-of-its-Kind Major Technical Equipment in China’s national energy sector. For the first time, it enables real-time perception and proactive early warning of operational risks in large-scale energy storage power stations, marking a significant breakthrough in intelligent safety early-warning technologies for energy storage facilities in China and underscoring the technological capabilities of the SGIT brand.

Innovation in System Architecture

The device adopts a cloud–edge–terminal collaborative architecture, integrating the acquisition, processing, and analysis of multi-level operational data across cells, clusters, systems, and power stations. By establishing a cyber-physical model and combining rapid computation at the edge with global analysis and strategy optimization in the cloud, it forms an intelligent early-warning system tailored to the operational characteristics of large-scale energy storage power stations.

Breakthrough in Core Algorithms

The device has developed a multi-dimensional state assessment and risk identification methodology that integrates physical mechanism models, data-driven models, and knowledge-graph-based reasoning. With the introduction of temporal correlation analysis and abnormal evolution identification mechanisms, the system enables early detection and tiered warnings of potential risks in energy storage systems. Compared with traditional threshold-based alarms, it significantly improves the accuracy and reliability of risk identification.

Validation and Application Results

In practical applications, the device has demonstrated stable support for concurrent access across multiple power stations and the early identification of various abnormal operating conditions. It has established a complete end-to-end technical framework covering data perception, state assessment, risk early warning, and operational decision support, providing a replicable and scalable technical pathway for the safe operation and intelligent O&M of large-scale energy storage power stations.

Media Contact
Company Name: SGIT
Contact Person: Yonghao Jiang
Email: Send Email
Country: China
Website: http://www.sgitg.sgcc.com.cn