Research on the identification of key factors in the construction of waste battery recycling system

Yanming Jin; Zhuonan Li; Xinli Xiao; Min Liu; Lingyu Chen

doi:10.1117/12.2636785

29 April 2022 Research on the identification of key factors in the construction of waste battery recycling system

Yanming Jin, Zhuonan Li, Xinli Xiao, Min Liu, Lingyu Chen

Proceedings Volume 12247, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2022); 1224721 (2022) https://doi.org/10.1117/12.2636785
Event: 2022 International Conference on Image, Signal Processing, and Pattern Recognition, 2022, Guilin, China

Abstract

With the large-scale development of new energy in China, large-scale energy storage batteries will be decommissioned. Most of the decommissioned batteries of power grid companies are located in substations, which involve a wide range of branches and a large number of sites but a small total. It also determines that it does not have strong competitiveness in commercial competition. Therefore, it is necessary to study the construction of energy storage battery recycling and reuse system in advance, evaluate the commercial value, and reduce recycling cost, especially for the key links in the recycling and reuse process, to conduct targeted optimization work. This paper focuses on the problems faced by the energy storage battery recycling of power grid companies, proposes an identification model for the key factors in the recycling system of used batteries for power grid companies. Finally, this paper proposes seven elements for the construction of a business model of hazardous waste recycling and reuse, and describes their interrelationships, which provides a reference for the recycling and reuse of hazardous wastes in power grid enterprises.

Citation Download Citation

Yanming Jin, Zhuonan Li, Xinli Xiao, Min Liu, and Lingyu Chen "Research on the identification of key factors in the construction of waste battery recycling system", Proc. SPIE 12247, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2022), 1224721 (29 April 2022); https://doi.org/10.1117/12.2636785

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