Study on the economic benefits of retired electric vehicle batteries participating in the electricity markets

JOURNAL OF CLEANER PRODUCTION

卷:286

Article

Xu, Xiao¹  Hu, Weihao¹  Liu, Wen²  Wang, Daojuan³  Huang, Qi¹  Chen, Zhe⁴ 

[1] Univ Elect Sci & Technol China, Sch Mech & Elect Engn, Sichuan Prov Key Lab Power Syst Wide Area Measure, Chengdu, Peoples R China

[2] Univ Utrecht, Copernicus Inst Sustainable Dev, Princetonlaan 8a, NL-3584 CB Utrecht, Netherlands

[3] Aalborg Univ, Business Sch, Fibigerstr 11-29, Aalborg, Denmark

[4] Aalborg Univ, Dept Energy Technol, Pontoppidanstr 111, Aalborg, Denmark

关键词: Economic benefit;    Retired electric vehicle batteries;    Electricity market;    Simulated annealing based particle swarm optimization;    Rainflow counting method;   

DOI  :  10.1016/j.jclepro.2020.125414

来源: Elsevier

【 摘 要 】

The lithium-ion batteries of battery electric vehicles are generally replaced when their capacity decays below 80% of the rated capacity. In this way, a large number of retired electric vehicle batteries (REVB) will be produced in a short time and cause new environmental pollution if REVB are not treated properly. To address this problem, one of the major solutions is to realize the echelon utilization of REVB based on the requirements of different application scenarios. Therefore, this study investigates the economic benefits of REVB participating in different Danish electricity markets. The objective function maximizes the profit in the different markets with considering REVB life loss cost in the operational process. Rainflow counting method is employed to accurately estimate the REVB life loss cost, leading to a strong nonlinearity of the optimization problem. Afterward, simulated annealing based particle swarm optimization (SAPSO) method is used to solve the nonlinear problem and find the optimal operational strategies of the REVB. Finally, a case study with considering different situations is provided to analyze the economic benefits of applying REVB in different markets. The results reveal: 1) SAPSO method performs best in finding the optimal results compared with particle swarm optimization and simulated annealing methods, and 2) It is more likely and beneficial to invest in REVB to participate in the regulation market than the day-ahead market. This significance of the study can be summarized as: 1) Theoretically, apart from proposing a simple, cheap and eco-friendly green strategy, i.e., the echelon utilization of REVB in Danish electricity market, we advance the knowledge and call for attention about under which conditions that performing a green strategy can allow environmental-economic benefits simultaneously achievable. 2) The study provides new business opportunities for energy storage and new energy industries, and can help to realize sustainable development to improve people's life and environmental quality. (C) 2020 Elsevier Ltd. All rights reserved.

【 授权许可】

Free