On-site at GGII Annual Conference! Ligoo’s AI Cloud Platform Safeguards Safe and Efficient Operation of Energy Storage Systems
From December 11 to 13, the 2024 GGII Energy Storage and GGII Gold Globe Awards Ceremony was grandly held in Shenzhen, with 1000+ upstream and downstream energy storage enterprises gathering to discuss industry focal issues.
Dr. Shen Yongbai, Dean of Ligoo New Energy Research Institute, delivered a keynote report titled “AI Cloud Platform Safeguards Safe and Efficient Operation of Energy Storage Systems,” discussing with industry experts and peers how to use big data to improve the economic benefits and safety performance of energy storage.
“Upholding Integrity and Seeking Change, Breaking Through Involution to Build Strength” was the theme of the GGII Energy Storage 2024 Annual Conference. Along with energy storage accelerating as an important support for new energy, the energy storage industry has entered a critical development period. While opportunities are surging, the periodic development laws of the industry are evident, and involution (cut-throat competition) has further intensified, urgently requiring joint industry efforts to respond to energy storage involution with integrity and innovation, and to jointly seek a development path.
At the annual conference, Dr. Shen delivered a keynote report, comprehensively elaborating on 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 in the report that the sustainable development of the energy storage industry cannot be separated from the two major themes of safety and revenue.
The new energy storage industry is highly competitive, but the risks of safety and revenue have also become prominent, affecting the confidence in industry development.
Thermal runaway accidents occur from time to time, and the current profit model is relatively singular, with unplanned outages accounting for nearly half, lifetimes generally falling short of expectations, and operational revenue facing challenges.
How to effectively reduce the risks of safety and revenue has become an urgent problem to be solved.
Based on the market’s higher requirements for the safety performance and economic benefits of energy storage systems, the company independently built an AI cloud platform to support system operation.
1 Earliest 60-Day-Ahead Battery Failure Warning
The AI cloud platform can generate AI models through the platform’s big data, accurately identifying battery anomalies. To date, the platform has built-in 50+ advanced AI algorithms, intelligently adapting to actual operating conditions, ensuring the accuracy of battery state estimation and the effective execution of control strategies, with a warning accuracy of 99% and a recall rate of 90%, achieving safety warnings up to 60 days ahead and generally over 30 days.
In addition, relying on the powerful performance and efficient algorithms of the big data platform, single-cell-level state prediction can be achieved, precisely identifying cell problems and minimizing the scope of issues.
2 Advanced Thermal Runaway Early Warning
Different from the traditional passive protection approach to thermal runaway, the AI cloud platform trains models through high-order algorithms, compares operating performance with the model’s expected performance, actively identifies data anomalies, and reports them in advance.
3 Intelligent Balancing to Improve Energy Utilization
The snapshot-based balancing of traditional BMS can only ensure that the battery’s voltage or SOC is consistent at the moment of calculation balancing, and cannot guarantee the maximization of the overall energy utilization of the system.
The AI cloud platform adopts an intelligent balancing algorithm, monitors abnormal cells, promptly adjusts consistency, and ensures the maximization of overall energy utilization.
4 Optimize SOP Curve to Maximize Operational Revenue
The AI cloud platform can also add value in the full-lifecycle management of battery parameters.
As the system runs for more years, the battery ages and its SOP curve gradually declines.
Through the AI cloud platform, SOP can be adjusted in real time according to the battery’s operating conditions, solving the mismatch between battery parameters and actual conditions, achieving the best match between operating conditions and battery life, and maximizing operational revenue.
Through the upgrading and transformation of traditional energy storage systems, Ligoo’s AI cloud platform introduces big data, artificial intelligence, cloud computing, and other technologies to complete the IoT upgrade of energy storage systems, supporting intelligent O&M functions such as model optimization, parameter tuning, advance warning, and predictive maintenance, safeguarding the safe and efficient operation of energy storage systems.
