双碳目标下电力系统转型对产业部门影响评估——以粤港澳大湾区为例

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Abstract This paper develops an empirical assessment of low-carbon electricity transition in China, with specific emphasis on identifying its impact on the industrial sectors associated with three alternative scenarios-baseline, carbon neutrality (CN) and enhanced carbon neutrality (ECN). The case in point for this assessment is provided by Guangdong-Hong Kong-Macao Greater Bay Area (thereafter, the Greater Bay Area). The analytical framework for this assessment is based on a dynamic CGE model. The results suggest that attaining net-zero electricity by 2045 (CN scenario) is likely to reduce energy consumption and CO₂ emissions by 8.9% and 67%, respectively, for the Greater Bay Area when compared with the baseline scenario. This impact would worsen the region’s reliance on electricity imports, adversely affecting its economic growth (3.9% less than the baseline scenario). This economic impact would, however, vary significantly across industrial sectors, reflecting their difference in terms of electric energy substitution, carbon emission reduction contribution and value-added flexibility. The impact on high electricity-dependent sectors is likely to be small (losses of about 79billion yuan in sectoral value-added), when compared with those sectors that are less dependent on electricity (losses of 100billion to 320billion yuan in sectoral value-added). By implication, this suggests that policymakers should consider promoting electrification and fuel-switching in these sectors, in order to reduce the adverse impact of electricity decarbonisation on their future growth. The electricity sector in the Greater Bay Area will attain net-zero emissions by 2040 in the ECN scenario. The strong growth of local renewable generation in this scenario could help reduce the region’s reliance on electricity imports (11% less than the CN scenario), contributing to energy security and socio-economic development (1.5% higher than the CN scenario). This development would particularly benefit industrial sectors that are highly dependent on electricity and promote electrification in other sectors

Key words： Guangdong-Hong Kong-Macao Greater Bay Area hybrid dynamic CGE model power system transition dual carbon target industrial sector

Received: 27 July 2021

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X321

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	XU Hong-wei
	WANG Peng
	REN Song-yan
	LIN Ze-wei
	ZHANG Cong
	ZHAO Dai-qing

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XU Hong-wei,WANG Peng,REN Song-yan等. Impact assessment of power system transition on industrial sectors under dual carbon targets——Take the Greater Bay Area as an example[J]. CHINA ENVIRONMENTAL SCIENCECE, 2022, 42(3): 1435-1445.

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http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2022/V42/I3/1435

[1]	国家可再生能源中心.美丽中国2050年的能源生态系统[R/OL]. 2018[2020-01-01]. https://max.book118.com/html/2018/0420/162194247.shtm.National Renewable Energy Center. Beautiful China's energy ecosystem in 2050[R/OL]. 2018[2020-01-01]. https://max.book118.com/html/2018/0420/162194247.shtm.
[2]	项目综合报告编写组.《中国长期低碳发展战略与转型路径研究》综合报告[J].中国人口·资源与环境, 2020,30(11):1-25. The Report of"China's Long-term low-carbon Development Strategy and Transformation Path"[J]. China Population, Resources and Environment, 2020,30(11):1-25.
[3]	周孝信.能源转型中我国新一代电力系统技术发展趋势[J].电气时代, 2018,(1):33-35. Zhou X X. Development trend of China's new generation power system technology in energy transition[J]. Electric Times, 2018,(1):33-35.
[4]	张宁,邢璐,鲁刚.我国中长期能源电力转型发展展望与挑战[J].中国电力企业管理, 2018,(13):58-63. Zhang Ning, Xing Lu, Lu Gang.Prospects and challenges of China's mid-and long-term energy and electric power transition development[J]. China Electric Power Enterprise Management, 2018,(13):58-63.
[5]	张运洲,张宁,代红才,等.中国电力系统低碳发展分析模型构建与转型路径比较[J].中国电力, 2021,54(3):1-11. Zhang Yun-zhou, Zhang Ning, DAI Hong-cai, et al. Model Construction and Pathways of Low-Carbon Transition of China's Power System[J]. China Electric Power, 2021,54(3):1-11.
[6]	姜红丽,刘羽茜,冯一铭,等.碳达峰、碳中和背景下"十四五"时期发电技术趋势分析[J].发电技术:1-12[2021-12-31]. http://kns.cnki.net/kcms/detail/33.1405.TK.20211230.1108.006.html. Jiang Hong-li, LIU Yu-qian, FENG Yi-Ming, et al. Analysis of power generation technology trend in 14th five-year plan under the background of carbon peak and carbon neutral[J]. Power generation technology:1-12[2021-12-31]. http://kns.cnki.net/kcms/detail/33.1405.TK.20211230.1108.006.html.
[7]	O'ryan Raúl, Nasirov Shahriyar,Álvarez-Espinosa Andrés. Renewable energy expansion in the chilean power market:A dynamic general equilibrium modeling approach to determine CO2 emission baselines[J]. J. Clean Prod., 2020,247:119645.
[8]	Yang Xi, Pang Jun, Teng Fei, et al. The environmental co-benefit and economic impact of China's low-carbon pathways:Evidence from linking bottom-up and top-down models[J]. Renewable and Sustainable Energy Reviews, 2021,136:110438.
[9]	Li Wei, Lu Can, Zhang Yan-Wu. Prospective exploration of future renewable portfolio standard schemes in China via a multi-sector CGE model[J]. Energy Policy, 2019,128:45-56.
[10]	Mu Yaqian, Cai Wenjia, Evans Samuel, et al. Employment impacts of renewable energy policies in China:A decomposition analysis based on a CGE modeling framework[J]. Applied Energy, 2018,210:256-267.
[11]	《粤港澳大湾区能源转型中长期情景研究》项目组.粤港澳大湾区能源转型中长期情景研究)[M].北京:科学出版社, 2020. Project group of《Mid-and long-term Scenario Study on Energy Transformation of Guangdong-Hong Kong-Macao Greater Bay Area》. Medium-and long-term scenario study of energy transformation in Guangdong-Hong Kong-Macao Greater Bay Area[M]. Beijing:Science Press, 2020.
[12]	南方电网能源发展研究院.粤港澳大湾区能源规划研究[R].广州:南方电网能源发展研究院有限责任公司, 2020. China Southern Power Grid Energy Development Research Institute. Energy planning in guangdong-Hong Kong-Macao Greater Bay Area[R]. Guangzhou:China Southern Power Grid Energy Development Research Institute Co., LTD., 2020.
[13]	Ian Sue Wing. The synthesis of bottom-up and top-down approaches to climate policy modeling:Electric power technologies and the cost of limiting US CO2 emissions[J]. Energy Policy, 2006,34(18):3847-3869.
[14]	Ian Sue Wing. The synthesis of bottom-up and top-down approaches to climate policy modeling:Electric power technology detail in a social accounting framework[J]. Energy Economics, 2008,30(2):547-573.
[15]	广东省统计局.广东省统计年鉴2018[M].北京:中国统计出版社, 2018. Statistics Bureau of Guangdong Province. Statistical yearbook of Guangdong Province 2018[M]. Beijing:China Statistics Press, 2018.
[16]	澳门统计局.澳门统计年鉴[R]. 2016-2019[2021-01-03]. http://www.tjcn.org/tjnj/33am/37957.html. Macao Statistical Bureau. Macao Statistical Yearbook[R]. 2016-2019[2021-01-03]. http://www.tjcn.org/tjnj/33am/37957.html.
[17]	经济合作与发展组织.香港投入产出表2015[EB/Z]. 2018[2021-01-08]. https://stats.oecd.org/Index.aspx?DataSetCode=IOTSI4_2018. Organization for Economic Cooperation and Development. Hong Kong input-output table 2015[EB/Z]. 2018[2021-01-08]. https://stats.oecd.org/Index.aspx?DataSetCode=IOTSI4_2018.
[18]	澳门统计年鉴委员会.澳门能源统计[R].澳门:统计局, 2016-2019. https://www.dsec.gov.mo/ts/#!/step1/zh-MO. Macao Statistical Yearbook Committee. Energy statistics of Macao[R]. Macao:Bureau of Statistics, 2016-2019. https://www.dsec.gov.mo/ts/#!/step1/zh-MO.
[19]	香港特别行政区政府统计处.香港能源统计2016年年刊[EB/OL]. https://www.censtatd.gov.hk/hkstat/sub/sp90_tc.jsp?productCode=B1100002. Census and Statistics Department, Hksar Government. Hong Kong energy statistics 2016 annual journal[EB/OL]. https://www.censtatd.gov.hk/hkstat/sub/sp90_tc.jsp?productCode=B1100002.
[20]	Ministry of Science and Technology, Economy and Energy. Supply of an instrument for estimating the emissions of green house effect gases coupled with the energy matrix[R/OL]. 2010[2014-06-11]. http://ecen.com/matriz/eee24/coefycin.htm.
[21]	广东省人民政府关于印发《广东省国民经济和社会发展第十三个五年规划纲要》的通知[J].广东省人民政府公报, 2016:3. People's Government of Guangdong Provincial. Notice of the People's government of Guangdong Province on printing and distributing the 13th five-year plan of Guangdong Province for national economic and social development[J]. Bulletin of Guangdong Provincial People's Government, 2016:3.
[22]	广东省人民政府关于印发广东省人口发展规划(2017~2030年)的通知[J].广东省人民政府公报, 2018,(7):3-28. People's Government of Guangdong Provincial. The People's government of Guangdong Province on the issuance of Guangdong Province population development plan (2017~2030)[J]. Bulletin of Guangdong Provincial People's Government, 2018,(7):P.3-28.
[23]	广东省发展和改革委员会.广东省能源发展"十二五"规划[EB/OL]. 2013[2014-07-01]. http://www.gddpc.gov.cn/fgzl/fzgh/zxgh/sewzx/201309/t20130926_220199.htm. Guangdong Provincial Development and Reform Commission. Energy development"twelfth five-year" plan of Guangdong Province[EB/OL]. 2013[2014-07-01]. http://www.gddpc.gov.cn/fgzl/fzgh/zxgh/sewzx/201309/t20130926_220199.htm.
[24]	香港特别行政区政府新闻公报.香港气候行动蓝图2030+[EB/OL]. 2017[2021-01-10]. https://sc.isd.gov.hk/TuniS/www.info.gov.hk/gia/general/201701/20/P2017012000724.htm?fontSize=1. Hong Kong Special Administrative Region Government Press Release. Hong Kong climate action blueprint 2030+[EB/OL]. 2017[2021-01-10]. https://sc.isd.gov.hk/TuniS/www.info.gov.hk/gia/general/201701/20/P2017012000724.htm?fontSize=1.
[25]	许鸿伟,汪鹏,任松彦,等.基于CGE模型的电力低碳转型速度调控策略研究——以粤港澳大湾区为例[J/OL].气候变化研究进展, 1-18[2021-12-31].http://kns.cnki.net/kcms/detail/11.5368.P.20211224.1634.004.html. Xu Hong-wei, Wang Peng, Ren Song-yan, et al. Research on the speed control strategy of low carbon power transition based on CGE model-take the GBA as an example[J/OL]. Advances in Climate Change Research.1-18[2021-12-31]. http://kns.cnki.net/kcms/detail/11.5368.P.20211224.1634.004.html.