Employing spatio-temporal analysis and multi-period location to optimize waste photovoltaic recycling network

被引:1
|
作者
Weng, Jingxue [1 ,2 ]
Zhang, Libo [2 ,3 ]
Tang, Jialin [2 ,3 ]
Wang, Qunwei [2 ,3 ]
Zhou, Dequn [2 ,3 ]
机构
[1] Tsinghua Univ, Shenzhen Int Grad Sch, Div Logist & Transportat, Shenzhen 518055, Peoples R China
[2] Nanjing Univ Aeronaut & Astronaut, Res Ctr Soft Energy Sci, Nanjing 211106, Peoples R China
[3] Nanjing Univ Aeronaut & Astronaut, Coll Econ & Management, Nanjing 211106, Peoples R China
基金
中国国家自然科学基金;
关键词
Waste PV modules; Recycling network; Spatio-temporal characterization; Dynamic location; Triple bottom line; REVERSE LOGISTICS; EMERGING WASTE; DESIGN; PROJECTION;
D O I
10.1016/j.seta.2024.103881
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
China has reached the cumulative installed capacity of 471 GW for photovoltaic (PV) power generation by mid2023, a development anticipated to result in a significant accumulation of waste PV modules. Analysis about spatio-temporal features of waste PV modules is a crucial step toward the development of efficient recycling network and the maximization of collection rate. We first employ the GM(1,1) model and the Weibull distribution to forecast that the quantity of scrap in China until 2040 will reach 700 GW. The study further estimates spatial distribution of wastes using hotspot analysis. Based on spatio-temporal distribution, this study extends the multi-period dynamic location model (MPDLM) for the recycling network of waste PV modules by incorporating the Triple Bottom Line (TBL) approach to minimize economic-environmental-social comprehensive cost and robust optimization for recycling demand uncertainty. A test conducted in the context of East China validates the effectiveness of the model, and the minimum cost 4.67354 x 107 CNY of dynamic location demonstrates the potential for practical value and cost savings about 80 % of multi-period compared with single-period model. This study can serve as a reference for relevant departments in formulating policies, as well as for recycling enterprises in making informed investment decisions.
引用
收藏
页数:13
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