Abstract:
Objective This study addresses the issues of varying quality in safety risk early warning technologies for lithium battery energy storage stations and the conceptual confusion between "early warning" and "alarming." It aims to clarify the connotation and stage-specific characteristics of risk early warning and to standardize technology application.
Method The research analyzed the connotation of station safety protection and investigated the causes of risk sources. It derived a development map for thermal runaway accidents in lithium batteries, defining characteristic signals and alert response measures for each stage. A systematic comparison was conducted between two categories of warning technologies: those based on external signals (particles, temperature, gas, stress, sound, ultrasonic) and those based on operational data analysis (voltage, current, temperature), focusing on their principles, applicable stages, and performance. Engineering application scenarios were statistically reviewed. The effectiveness of a specific early warning technology was validated using data from actual engineering project deployments.
Result The study clarifies the development stages of safety risks, their characteristic signals, and a graded alert notification mechanism, fundamentally distinguishing "early warning" (targeting early-stage risks) from "alarming" (triggered post-thermal runaway). The technology comparison demonstrates: external signal-based technologies are only suitable for post-thermal runaway alarming; operational data analysis technologies enable risk early warning across all accident stages, including early abnormalities. A market phenomenon exists where alarming technologies are misleadingly promoted as early warning solutions. Engineering application data confirms: the adoption of full-stage early warning technology significantly reduces the occurrence probability of safety risk incidents in stations. Based on this data, a risk probability classification is established.
Conclusion Operational data analysis-based early warning technology is an effective means for achieving full-stage risk early warning in lithium battery energy storage stations, exhibiting significantly superior performance compared to external signal-based alarming technologies. Market promotion must be regulated, strictly differentiating between early warning and alarming functions. The proposed risk development map, signal identification framework, and graded alert mechanism lay the foundation for an early warning system. Engineering practice should prioritize the selection of full-stage early warning technologies compliant with standards. Actual data validates its effectiveness in significantly reducing risk probability, and the resulting risk classification provides crucial evidence for safety management. Further research into intelligent algorithms and the promotion of technology standardization is recommended.