| Title |
Comparative life cycle greenhouse gas emissions assessment of battery energy storage technologies for grid applications |
| ID_Doc |
68169 |
| Authors |
Han, XQ; Li, YX; Nie, L; Huang, XF; Deng, YL; Yan, JJ; Kourkoumpas, DS; Karellas, S |
| Title |
Comparative life cycle greenhouse gas emissions assessment of battery energy storage technologies for grid applications |
| Year |
2023 |
| Published |
|
| DOI |
10.1016/j.jclepro.2023.136251 |
| Abstract |
With an ever-increasing penetration of renewable energy sources into the power grid, the development and commercialization of large-scale energy storage systems (ESSs) have been enforced. It is imperative to evaluate the environmental sustainability of ESSs in grid applications to achieve sustainable development goals. In the present work, a cradle-to-grave life cycle analysis model, which incorporates the manufacturing, usage, and recycling processes, was developed for prominent electrochemical energy storage technologies, including lithium iron phosphate batteries (LIPBs), nickel cobalt manganese oxide batteries (NCMBs), and vanadium redox flow batteries (VRFBs). A case study was conducted based on per MWh of energy stored. The greenhouse gas (GHG) emissions of LIPBs, NCMBs, and VRFBs under the Chinese electrical grid peak-shaving scenario were determined to be 323, 263, and 425 kg CO2-eq/MWh, respectively. The key components contributing to the GHG emissions were identified. The GHG emissions of different batteries in renewable energy sources (photovoltaic and wind) were evaluated. Moreover, the GHG emissions under the future electricity mixes were predicted according to the carbon peaking and carbon neutrality goals. The GHG emissions of LIPBs, NCMBs, and VRFBs under the Announced Pledges Scenario could be reduced by approximately 23-27% in 2030 and 66-75% in 2050. Moreover, sensitivity analysis was performed, indicating that the GHG emissions were directly linked with the round-trip efficiency. The results could promote the environment, policy, and business model optimization ef-forts for large-scale energy storage in low-carbon power systems. |
| Author Keywords |
Energy storage; Battery; Life cycle assessment; Greenhouse gas emissions |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000994391000001 |
| WoS Category |
Green & Sustainable Science & Technology; Engineering, Environmental; Environmental Sciences |
| Research Area |
Science & Technology - Other Topics; Engineering; Environmental Sciences & Ecology |
| PDF |
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