我校偷情自拍 於世为老师在T1级别期刊——《APPLIED ENERGY》上发表题为“Multi-objective optimization of capacity and technology selection for provincial energy storage in China: The effects of peak-shifting and valley-filling”。论文第一作者於世为为偷情自拍 教授、博士生导师。
Abstract / 摘要:
To support long-term energy storage capacity planning, this study proposes a non-linear multi-objective planning model for provincial energy storage capacity (ESC) and technology selection in China. The model aims to minimize the load peak-to-valley difference after peak-shaving and valley-filling. We consider six existing mainstream energy storage technologies: pumped hydro storage (PHS), compressed air energy storage (CAES), super-capacitors (SC), lithium-ion batteries, lead-acid batteries, and vanadium redox flow batteries (VRB). The optimized results show that 1) the accumulated ESC in China could increase at an average annual rate of 14.4–17.6% in 2020–2035, reaching 271.1–409.7 GW in 2035 at a total cost of 34.9–41.6 trillion yuan. 2) With favorable technical development levels and application prospects, lithium-ion batteries will be the dominant technology in 2035 in all scenarios. SC has the fastest growth rate among the six technologies in most scenarios because of its flexible location and long lifetime. 3) In the BAU scenario, Xinjiang, Inner Mongolia, Hebei, Ningxia, and Qinghai are the provinces with the largest ESC in 2035 while the four municipalities of Chongqing, Beijing, Tianjin, and Shanghai, as well as Tibet, have the smallest. This layout depends on the differences in the installed capacity of renewable energy in the provinces.
论文信息;
Title/题目:
Multi-objective optimization of capacity and technology selection for provincial energy storage in China: The effects of peak-shifting and valley-filling
Authors/作者:
Yu, Shiwei; Zhou, Shuangshuang; Chen, Nan
Keyword / 关键词
Energy storage capacity;Technology selection;Renewable energy;Multi-objective optimization
Indexed by / 核心评价
EI;INSPEC;MEDLINE;SCI;Scopus;WAJCI
DOI:10.1109/TNNLS.2024.10064704
全文链接:
//libproxy.tqzp.org/https/443/org/ieee/ieeexplore/yitlink/document/10064704