锂电池储能电站安全风险预警技术及工程应用综述

王黎明; 史梓男; 李棉刚; 郭富民; 梁惠施; 林俊; 尹芳辉

doi:10.16516/j.ceec.2025-240

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锂电池储能电站安全风险预警技术及工程应用综述

新能源与储能系统 | 更新时间：2026-10-14

- 锂电池储能电站安全风险预警技术及工程应用综述
- Review of Safety Risk Early Warning Technology and Engineering Application for Lithium Battery Energy Storage Power Stations
- 南方能源建设 2026年13卷第4期页码：1-16
- 作者机构：
  
  1. 清华大学深圳国际研究生院,广东,深圳,518055
  2. 清华四川能源互联网研究院,成都,610042
  3. 山东电力工程咨询院有限公司,山东,济南,250013
- 作者简介：
  
  王黎明，BRID: 09086.00.685571963-，男，教授，博士生导师，研究方向为高电压外绝缘、特高压输电、电磁环境及电工新技术等（e-mail）wanglm@sz.tsinghua.edu.cn
  史梓男，1978-，男，正高级工程师，硕士，研究方向为电力系统储能主动安全（e-mail）shizinan@tsinghua-eiri.org
  李棉刚，（e-mail）limiangang@tsinghua-eiri.org
- 基金信息：
  
  广东省重点领域研发计划项目“构网型储能变流器关键技术及装备研究”（ 2023B0909030001）;内蒙古自治区“揭榜挂帅”项目“大规模电化学储能电站安全预警及风险监控研究”（2024JBGS0053）
- DOI：10.16516/j.ceec.2025-240
  中图分类号： TM912;TK02
- 纸质出版：2026
- 稿件说明：
移动端阅览
王黎明, 史梓男, 李棉刚, 等. 锂电池储能电站安全风险预警技术及工程应用综述[J]. 南方能源建设, 2026, 13(4): 1-16.

.
王黎明, 史梓男, 李棉刚, 等. 锂电池储能电站安全风险预警技术及工程应用综述[J]. 南方能源建设, 2026, 13(4): 1-16. DOI： 10.16516/j.ceec.2025-240.

. DOI： 10.16516/j.ceec.2025-240.

摘要

目的

针对锂电池储能电站安全风险预警技术质量差异及“预警”“报警”概念混淆问题，明确风险预警内涵与阶段性特征，规范技术应用。

方法

剖析电站安全防护内涵，梳理风险源成因；推导锂电池热失控事故发展图谱，界定各阶段特征信号与警情措施；系统比较基于外部信号（微粒子、温度、气体、应力、声音）与基于运行数据（电压、电流、温度）两类预警技术的原理、适用阶段及优劣；统计工程应用情况；基于实际工程项目应用数据验证特定预警技术效果。

结果

明确风险发展阶段、特征信号及分级通报机制，厘清“预警”（早期风险）与“报警”（热失控后）本质区别。技术比较表明：外部信号技术仅适用于热失控报警；运行数据分析技术可实现事故全阶段（含早期异常）预警。市场存在将报警技术误导宣传为预警技术的现象。工程应用数据证实：采用全阶段预警技术后，电站安全风险事件发生概率显著降低，据此完成风险概率分级。

结论

基于运行数据分析的预警技术是锂电池储能电站实现全阶段风险预警的有效手段，性能显著优于外部信号报警技术。须规范市场宣传并严格区分预警/报警功能。提出的风险图谱、信号识别及分级通报框架为预警体系奠定基础。工程应优先选用全阶段预警技术并符合标准。实际数据验证其显著降低风险概率，风险分级结果为安全管理提供关键依据。建议深化智能算法研究并推动技术标准化。

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 betwee

n 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.

关键词

Keywords

references

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