| Title |
A Study on Diagnosis Algorithm for Fire Accident Risk Based on Operation Environment Data in Energy Storage System |
| Authors |
최형석(Hyoung-Seok Choi) ; 이민행(Min-Haeng Lee) ; 장형안(Hyeong-An Jang) ; 김윤호(Yun-Ho Kim) ; 황소연(So-Yeon Hwang) ; 노대석(Dae-Seok Rho) |
| DOI |
https://doi.org/10.5370/KIEE.2026.75.8.1746 |
| Keywords |
Off-gas Detection Device; ESS; Li-ion Battery; Thermal Runaway; Prevent Fire; Venting |
| Abstract |
Recently, according to the government's green growth and carbon-neutral policy, large-scale energy storage system(ESS) has been rapidly installing and operating. However, the safety issues in ESS have been raising according to the severe damage to the entire industry with the total of around 60 fire accidents beginning in August 2017. And also, Li-ion battery-based ESS fire cases can lead to a rapid temperature rise and propagation to adjacent cells and modules due to thermal runaway characteristics, accordingly risk evaluation methods are being required on the pre and post fire case based on the operation environment data in ESS. Therefore, this paper presents the risk diagnosis algorithm of pre-post fire case in ESS based on ESS operation environment data such as temperature, humidity, oxygen, off-gas, pressure, dust, smoke, and so on, and implements a test device for ESS fire diagnosis which contains detection section, monitoring and control section, auxiliary device section. Where, the proposed risk diagnosis algorithm of pre-post fire case in ESS can evaluate the risk degree with fire scenarios in systematical manner by considering weighting factors based on the operation environment data in ESS. From the test results based on the proposed risk diagnosis algorithm of pre-post fire case in ESS, it is confirmed that the algorithm is expected to be an effective tool to effectively evaluate the risk degree of pre-post fire for both battery and non battery fire cases. |