TY - JOUR
T1 - Optimization of electricity generation and assessment of provincial grid emission factors from 2020 to 2060 in China
AU - Jia, Min
AU - Zhang, Zhe
AU - Zhang, Li
AU - Zhao, Liang
AU - Lu, Xinbo
AU - Li, Linyan
AU - Ruan, Jianhui
AU - Wu, Yunlong
AU - He, Zhuoming
AU - Liu, Mei
AU - Jiang, Lingling
AU - Gao, Yajing
AU - Wu, Pengcheng
AU - Zhu, Shuying
AU - Niu, Muchuan
AU - Zheng, Haitao
AU - Cai, Bofeng
AU - Tang, Ling
AU - Shu, Yinbiao
AU - Wang, Jinnan
PY - 2024/11/1
Y1 - 2024/11/1
N2 - The developmental trajectory of provincial power grids in alignment with dual‑carbon goals requires the systematical prediction of China's provincial power grids. In this study, a comprehensive electricity production optimization model covering all 31 provinces in mainland China is developed to simulate and optimize the provincial operation of the power sector for 2020–2060 under a reference scenario and two renewable energy development scenarios. Then, dynamic, province-specific, and yearly grid CO2 emission factors and relative direct and indirect emissions from both the producer and consumer sides are evaluated. We find significant increases in renewable energy installed capacity and power generation, with yearly growth rates of 6.40% and 5.29%, respectively, from 2020 to 2060. Solar and wind power generation will contribute the most to the national installed capacity and power generation (79.03% and 56.03%, respectively, in 2060). Notably, Inner Mongolia is projected to represent the majority of national solar and wind power generation, with the largest mitigation potential, but the highest grid CO2 emission factor. Substantial reductions in grid CO2 emission factors (by 12.54%) and associated CO2 emissions (by 19.73%) are linked to renewable energy development in the power sector. Our results help highlight the effectiveness of renewable energy development and facilitate future provincial policymaking. © 2024 Elsevier Ltd.
AB - The developmental trajectory of provincial power grids in alignment with dual‑carbon goals requires the systematical prediction of China's provincial power grids. In this study, a comprehensive electricity production optimization model covering all 31 provinces in mainland China is developed to simulate and optimize the provincial operation of the power sector for 2020–2060 under a reference scenario and two renewable energy development scenarios. Then, dynamic, province-specific, and yearly grid CO2 emission factors and relative direct and indirect emissions from both the producer and consumer sides are evaluated. We find significant increases in renewable energy installed capacity and power generation, with yearly growth rates of 6.40% and 5.29%, respectively, from 2020 to 2060. Solar and wind power generation will contribute the most to the national installed capacity and power generation (79.03% and 56.03%, respectively, in 2060). Notably, Inner Mongolia is projected to represent the majority of national solar and wind power generation, with the largest mitigation potential, but the highest grid CO2 emission factor. Substantial reductions in grid CO2 emission factors (by 12.54%) and associated CO2 emissions (by 19.73%) are linked to renewable energy development in the power sector. Our results help highlight the effectiveness of renewable energy development and facilitate future provincial policymaking. © 2024 Elsevier Ltd.
KW - Electricity transmission
KW - Generation optimization
KW - Grid emission factor
KW - Indirect emissions
KW - Power grid
UR - http://www.scopus.com/inward/record.url?scp=85198241852&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85198241852&origin=recordpage
U2 - 10.1016/j.apenergy.2024.123838
DO - 10.1016/j.apenergy.2024.123838
M3 - RGC 21 - Publication in refereed journal
SN - 0306-2619
VL - 373
JO - Applied Energy
JF - Applied Energy
M1 - 123838
ER -
