From December 11 to 13, the 2024 GGII Energy Storage Conference and GGII Gold Globe Awards ceremony was grandly held in Shenzhen, bringing together more than 1,000 upstream and downstream enterprises across the energy storage industry chain to discuss key sector issues. Dr. Shen Yongbai, Dean of LIGOO’s Research Institute, delivered a keynote report titled “AI Cloud Platform Safeguards Safe and Efficient Energy Storage Operation,” joining industry experts to explore how big data can improve the economic benefits and safety performance of energy storage.
Industry Context
“Upholding the fundamentals while embracing change, breaking through involution to build strength” was the theme of the 2024 GGII Energy Storage Annual Conference. As energy storage rapidly becomes a critical pillar of new energy, the industry has entered a pivotal development phase. Alongside surging opportunities, pronounced cyclical dynamics and intensifying “involution” (cut-throat competition) demand collective industry effort to respond with steadfast innovation and chart a shared path forward.
At the conference, Dr. Shen delivered the keynote, comprehensively explaining the significance of the company’s self-developed AI cloud platform for the safe and efficient operation of energy storage systems. Dr. Shen first pointed out that the sustainable development of the energy storage industry hinges on two central themes: safety and revenue.
The emerging storage industry is highly competitive, yet risks to safety and revenue have become increasingly prominent, undermining confidence in the sector’s development. Thermal-runaway incidents occur from time to time; current profit models are relatively singular, unplanned outages account for nearly half of cases, service life generally falls short of expectations, and operating returns face challenges. Effectively reducing the risks to safety and revenue has thus become an urgent issue to address.
In response to the market’s higher demands for safety and economic performance, the company built its own AI cloud platform to support system operation.
Battery Fault Warning up to 60 Days in Advance
The AI cloud platform generates AI models from platform big-data to accurately identify battery anomalies. To date, the platform has built in 50+ advanced AI algorithms that intelligently adapt to actual operating conditions, ensuring accurate battery state estimation and effective control-strategy execution. With a warning accuracy of 99% and a recall of 90%, it achieves safety early-warnings up to 60 days in advance (generally over 30 days).
Moreover, leveraging the big-data platform’s powerful performance and efficient algorithms, it can perform cell-level state prediction, precisely identifying cell issues and minimizing their scope.
Advanced Thermal-Runaway Early Warning
Unlike traditional passive thermal-runaway protection, the AI cloud platform uses advanced algorithms to train models that compare actual operating performance against expected model behavior, proactively detecting data anomalies and issuing early alerts.
Intelligent Balancing to Improve Energy Utilization
Traditional BMS snapshot-based balancing only ensures that voltage or SOC is consistent at the moment of balancing calculation, and cannot maximize the overall energy utilization of the system. The AI cloud platform adopts intelligent balancing algorithms that monitor anomalous cells and adjust consistency in real time, ensuring maximum overall energy utilization.
Optimizing the SOP Curve to Maximize Operating Revenue
The AI cloud platform also adds value to full-lifecycle management of battery parameters. As a system ages with years of operation, battery degradation gradually lowers its SOP (State of Power) curve. Through the AI cloud platform, SOP can be adjusted in real time based on actual battery operation, resolving the mismatch between battery parameters and real conditions, achieving the optimal match between operating scenarios and battery life, and maximizing operating revenue.
Platform Value
By upgrading traditional energy storage systems, LIGOO’s AI cloud platform introduces big data, AI, and cloud computing to complete the IoT upgrade of storage systems, supporting intelligent O&M functions such as model optimization, parameter tuning, early warning, and predictive maintenance, thereby safeguarding safe and efficient energy storage operation.
