Optimization of electricity generation and assessment of provincial grid emission factors from 2020 to 2060 in China

Min Jia, Zhe Zhang, Li Zhang, Liang Zhao, Xinbo Lu, Linyan Li, Jianhui Ruan, Yunlong Wu, Zhuoming He, Mei Liu, Lingling Jiang, Yajing Gao, Pengcheng Wu, Shuying Zhu, Muchuan Niu, Haitao Zheng, Bofeng Cai, Ling Tang, Yinbiao Shu and Jinnan Wang

Applied Energy, 2024, vol. 373, issue C, No S0306261924012212

Abstract: 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.

Keywords: Power grid; Generation optimization; Electricity transmission; Grid emission factor; Indirect emissions (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.apenergy.2024.123838

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