Driven by “carbon peaking and carbon neutrality” strategic goals in China, energy storage stations have become a critical component in promoting the transition to new energy. Lithium-ion battery storage is developing at the fastest pace, with its total capacity expected to grow significantly during the 14th Five-Year Plan period. However, the problems of thermal runaway early warning and fire suppression in large-scale lithium-ion battery energy storage systems are still unresolved. As a result, fire or explosion incidents caused by thermal runaway often occur.
According to incomplete figures, more than 50 fire incidents at energy storage stations have occurred globally in the past decade, producing negative influence on the industry development. In China, the most notable incident was the “April 16” event in Beijing in 2021, where a fire and explosion resulted in 2 deaths, 1 injury, and 1 missing person. On January 12, 2022, a truck fully loaded with lithium batteries caught fire on the Jinggang’ao Expressway in Jiangxia District, Wuhan, due to internal thermal runaway. In the world, on July 30, 2021, a fire occurred during the commissioning of an energy storage project in Victoria, Australia, burning for four days before being extinguished. On January 12, 2022, a fire broke out at the SK Energy battery storage building in Ulsan, South Korea, followed just five days later by another fire of energy storage system at a solar power plant in Gunwi County, North Gyeongsang Province, caused by internal thermal runaway.
After the occurrence of the “April 16” incident in Beijing, the safety of lithium-ion battery energy storage has risen to an unprecedented level of importance, indicating the shortcomings of current safety prevention technologies. Therefore, two government ministries issued policies months later, calling for safety and online monitoring technologies as essential requirements. In response to these requirements, Wuhan CloudScout Science&Technology Co.,LTD has proposed an online monitoring solution for safety of lithium-ion battery energy storage stations. This solution is centered on proprietary nano-particle detection technology, and is also combined with multiple characteristic gas detection and artificial intelligence algorithms to monitor and provide early warnings for safety hazards in lithium-ion battery bodies, electrical equipment, and operating environments within energy storage systems. This significantly enhances the overall safety prevention capabilities of energy storage stations, reduces the probability of safety incidents, improves intelligent monitoring levels and operation efficiency, and relieves the burden of manual labor.
Key Features
01. Early Warning for Thermal Runaway of Battery Body
This function monitors particulate matter and multiple characteristic gases produced during battery thermal runaway. With the use of intelligent algorithm featuring multi-source data fusion, it realizes advanced warning during the initial stages of thermal runaway.
02. Monitoring and Early Warning of External Safety Hazards
This function monitors electrical equipment and operating environments outside the battery bodies, and identifies external safety hazards such as poor connections of external connectors, overheating and insulation defects, further realizing comprehensive online safety monitoring of the entire prefabricated container.
03. Active Detection
The active air sampling detection is adopted, showing faster response than traditional passive sensing or diffused detection methods, which is thereby very suitable for energy storage stations with rapid alarm response requirements.
