新形势下“十四五”后三年中国电力需求形势研判

doi:10.11930/j.issn.1004-9649.202302048

中国电力 ›› 2023, Vol. 56 ›› Issue (3): 1-11.DOI: 10.11930/j.issn.1004-9649.202302048

新形势下“十四五”后三年中国电力需求形势研判

单葆国¹, 刘青¹, 张莉莉¹, 郑海峰¹, 张成龙¹, 吴姗姗¹, 薛万磊²

1. 国网能源研究院有限公司，北京 102209;
2. 国网山东省电力公司经济技术研究院，山东济南 250021

收稿日期:2023-02-14 修回日期:2023-03-07 出版日期:2023-03-28 发布日期:2023-03-28
作者简介:单葆国(1971-),男,硕士,高级工程师(教授级),从事能源经济模型、电力市场分析预测、电力需求与经济发展关系、电力需求侧管理等研究,E-mail:shanbaoguo@sgeri.sgcc.com.cn;刘青(1994-),男,硕士,工程师,从事能源电力供需分析预测、节能节电与电能替代等研究,E-mail:liuqing@sgeri.sgcc.com.cn
基金资助:
国家电网有限公司科技项目（终端行业与电力行业碳减排路径协同优化模拟技术及应用研究，1400-202257250A-1-1-ZN）。

Analysis of China’s Power Demand Situation in the Last Three Years of the “14th Five-Year Plan” Under the New Situation

SHAN Baoguo¹, LIU Qing¹, ZHANG Lili¹, ZHENG Haifeng¹, ZHANG Chenglong¹, WU Shanshan¹, XUE Wanlei²

1. State Grid Energy Research Institute Co., Ltd., Beijing 102209, China;
2. Economic and Technology Research Institute, State Grid Shandong Electric Power Company, Jinan 250021, China

Received:2023-02-14 Revised:2023-03-07 Online:2023-03-28 Published:2023-03-28
Supported by:
This work is supported by Science & Technology Project of SGCC (Research and Application of Collaborative Optimization Simulation Technology of Carbon Emission Reduction Path between Terminal Industry and Power industry, No.1400-202257250A-1-1-ZN).

摘要/Abstract

摘要： 中国式现代化建设、“双碳”战略落地、新型电力系统构建、电力市场化改革推进等新形势将深刻影响未来中国电力需求形势。充分考虑新形势下宏观经济、技术进步、能源转型、电力市场、气候气温等影响电力需求的因素变化趋势，采用“经济-能源-电力-环境”耦合的中长期电力需求预测模型，设置3个情景，深入研判“十四五”后三年中国电力需求增长趋势。结果表明，2023、2024、2025年，中国全社会用电量分别为9.1万亿~9.3万亿、9.4万亿~9.7万亿、9.7万亿~10.1万亿kW·h，“十四五”年均增速为5.2%~6.0%。

关键词: 新形势, “十四五”, 电力需求, 预测

Abstract: The new situation, such as the construction of the Chinese modernization, implementation of the “double carbon” strategy, construction of the new power system, and promotion of power market-oriented reform, will profoundly affect future power demand situation in China. With full consideration of the changing trend of macroeconomics, technological progress, energy transformation, power market, climate and temperature and other factors affecting power demand under the new situation, the medium and long-term power demand forecasting model coupled with “economy-energy-electricity-environment” is adopted to analyze the growth trend of the China’s power demand in the last three years of the “14th Five-Year Plan” (2021-2025) under three scenarios. The results show that in 2023, 2024 and 2025, China’s total social electricity consumption will be 9.1 to 9.3 trillion, 9.4 to 9.7 trillion and 9.7 to 10.1 trillion kilowatt-hours respectively, with an annual growth rate of 5.2% to 6.0% in the “14th Five-Year Plan”.

Key words: new situation, 14th Five-Year Plan, power demand, forecast

单葆国, 刘青, 张莉莉, 郑海峰, 张成龙, 吴姗姗, 薛万磊. 新形势下“十四五”后三年中国电力需求形势研判[J]. 中国电力, 2023, 56(3): 1-11.

SHAN Baoguo, LIU Qing, ZHANG Lili, ZHENG Haifeng, ZHANG Chenglong, WU Shanshan, XUE Wanlei. Analysis of China’s Power Demand Situation in the Last Three Years of the “14th Five-Year Plan” Under the New Situation[J]. Electric Power, 2023, 56(3): 1-11.

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参考文献

[1] 辛保安, 单葆国, 李琼慧, 等. “双碳”目标下“能源三要素”再思考[J]. 中国电机工程学报, 2022, 42(9): 3117–3126
XIN Baoan, SHAN Baoguo, LI Qionghui, et al. Rethinking of the “three elements of energy” toward carbon peak and carbon neutrality[J]. Proceedings of the CSEE, 2022, 42(9): 3117–3126
[2] 单葆国, 冀星沛, 许传龙, 等. 近期全球能源供需形势分析及中国能源电力保供策略[J]. 中国电力, 2022, 55(10): 1–13
SHAN Baoguo, JI Xingpei, XU Chuanlong, et al. Recent situation of global energy supply-demand and guarantee strategy of China’s energy and power supply[J]. Electric Power, 2022, 55(10): 1–13
[3] 单葆国, 冀星沛, 姚力, 等. 能源高质量发展下中国电力供需格局演变趋势[J]. 中国电力, 2021, 54(11): 1–9,18
SHAN Baoguo, JI Xingpei, YAO Li, et al. Evolving tendency of electric supply and demand pattern under the circumstances of high-quality energy development[J]. Electric Power, 2021, 54(11): 1–9,18
[4] 谭显东, 刘俊, 徐志成, 等. “双碳”目标下“十四五”电力供需形势[J]. 中国电力, 2021, 54(5): 1–6
TAN Xiandong, LIU Jun, XU Zhicheng, et al. Power supply and demand balance during the 14 th five-year plan period under the goal of carbon emission peak and carbon neutrality[J]. Electric Power, 2021, 54(5): 1–6
[5] 苏步芸, 张英杰, 熊晓晟. 双碳、双区背景下深圳电力需求预测[J]. 南方能源建设, 2022, 9(4): 127–134
SU Buyun, ZHANG Yingjie, XIONG Xiaosheng. Power demand forecast in Shenzhen under the background of double carbon and double zones[J]. Southern Energy Construction, 2022, 9(4): 127–134
[6] 余潇潇, 宋福龙, 周原冰, 等. “新基建”对中国“十四五”电力需求和电网规划的影响分析[J]. 中国电力, 2021, 54(7): 11–17
YU Xiaoxiao, SONG Fulong, ZHOU Yuanbing, et al. Investigations on the impact of new infrastructure on electricity forecast and power system planning during the 14 th five-year plan period[J]. Electric Power, 2021, 54(7): 11–17
[7] 王宝, 马静, 叶斌, 等. 基于经济与气象维度影响因素的省级电网年度电力需求预测方法[J]. 电力需求侧管理, 2020, 22(2): 51–55, 61
WANG Bao, MA Jing, YE Bin, et al. Forecasting method of provincial grid’s annual power demand based on influencing factors from economic and meteorological dimensions[J]. Power Demand Side Management, 2020, 22(2): 51–55, 61
[8] 孙祥栋, 尹彦辉, 郑艳婷. 区域经济异质视角下电力消费因素分解及“拐点”分析[J]. 技术经济, 2019, 38(7): 100–108
SUN Xiangdong, YIN Yanhui, ZHENG Yanting. Electricity consumption decomposition and “inflection point” analysis considering heterogeneity of China’s regional economic growth[J]. Technology Economics, 2019, 38(7): 100–108
[9] IMF. World economic outlook[R].https://www.imf.org/en/Publications/WEO/Issues/2023/01/31/world-economic-outlook-update-january-2023.
[10] 国网能源研究院有限公司. 中国节能节电分析报告2019[M]. 北京: 中国电力出版社, 2020.
[11] 单葆国. 能效管理及节能服务产业发展研究[J]. 电气时代, 2021(4): 6–9
[12] 薛万磊, 唐伟, 徐楠, 等. 能耗电耗现状分析及“十四五”能效发展预判[J]. 电力需求侧管理, 2020, 22(6): 6–11
XUE Wanlei, TANG Wei, XU Nan, et al. Analysis of current situation of energy and electricity consumption and prediction of energy efficiency development during the 14 th five-year plan[J]. Power Demand Side Management, 2020, 22(6): 6–11
[13] 郑海峰. 数说我国电气化发展及未来[J]. 中国电力企业管理, 2022(34): 63–65
[14] 唐伟, 徐朝, 单葆国, 等. 基于细分行业用能结构特征的“十四五”电能替代电量规划[J]. 中国电力, 2021, 54(7): 36–45
TANG Wei, XU Zhao, SHAN Baoguo, et al. Electric energy substitution planning for the “14 th five-year plan” period based on characteristics of energy consumption structure of subdivided industries[J]. Electric Power, 2021, 54(7): 36–45
[15] 唐伟. 电能替代实施现状及发展趋势预判[J]. 中国能源, 2020, 42(2): 35–38, 47
TANG Wei. Current situation analysis and development trend prediction of electric energy substitution[J]. Energy of China, 2020, 42(2): 35–38, 47
[16] 廖智强, 莫秋云. 基于能量偿还时间的小型风力发电机预安装评估[J]. 科学技术与工程, 2020, 20(35): 14512–14517
LIAO Zhiqiang, MO Qiuyun. Pre-installation evaluation of small wind turbines based on energy pay back time[J]. Science Technology and Engineering, 2020, 20(35): 14512–14517
[17] 中华人民共和国工业和信息化部. 光伏制造行业规范条件(2021年本)[A].
[18] 潘光胜, 顾钟凡, 罗恩博, 等. 新型电力系统背景下的电制氢技术分析与展望[J/OL]. 电力系统自动化, 2023: 1–15. (2023-02-08).https://kns.cnki.net/kcms/detail/32.1180.TP.20230208.1033.001.html.
PAN Guangsheng, GU Zhongfan, LUO Enbo, et al. Analysis and prospect of electrolytic hydrogen technology under background of new power systems[J/OL]. Automation of Electric Power Systems, 2023: 1–15. (2023-02-08).https://kns.cnki.net/kcms/detail/32.1180.TP.20230208.1033.001.html.
[19] 蔡湛, 李泽文, 邹睿奇, 等. 基于负荷转移的售电公司分时电价优化策略[J/OL]. 南方电网技术, 2023: 1–8. (2023-01-20).https://kns.cnki.net/kcms/detail/44.1643.TK.20230119.1315.001.html.
CAI Zhan, LI Zewen, ZOU Ruiqi, et al. Optimization strategy of time-of-use electricity price of electricity sales companies based on load transfer[J/OL]. Southern Power System Technology, 2023: 1–8. (2023-01-20).https://kns.cnki.net/kcms/detail/44.1643.TK.20230119.1315.001.html.
[20] 周业荣, 毛玉鑫, 胡杨, 等. 2022年夏季极端天气对四川电力影响与启示[J/OL]. 水力发电学报, 2023: 1–7. (2023-01-03).https://kns.cnki.net/kcms/detail/11.2241.TV.20221230.1522.003.html.
ZHOU Yerong, MAO Yuxin, HU Yang, et al. Impact of extreme weather on Sichuan’ power in summer of 2022 and its enlightenment[J/OL]. Journal of Hydroelectric Engineering, 2023: 1–7. (2023-01-03).https://kns.cnki.net/kcms/detail/11.2241.TV.20221230.1522.003.html.
[21] 黄震, 谢晓敏, 张庭婷. “双碳”背景下我国中长期能源需求预测与转型路径研究[J]. 中国工程科学, 2022, 24(6): 8–18
HUANG Zhen, XIE Xiaomin, ZHANG Tingting. Medium- and long-term energy demand of China and energy transition pathway toward carbon neutrality[J]. Strategic Study of CAE, 2022, 24(6): 8–18
[22] 张运厚, 李婉莹, 董福贵. 基于DE-GWO-SVR的中长期电力需求预测[J]. 中国电力, 2021, 54(9): 83–88
ZHANG Yunhou, LI Wanying, DONG Fugui. Medium and long-term power demand forecasting based on DE-GWO-SVR[J]. Electric Power, 2021, 54(9): 83–88
[23] 王秋惠. 基于空间自回归模型的电力系统中长期负荷特性分析与预测[J]. 东北电力大学学报, 2021, 41(3): 118–123
WANG Qiuhui. The characteristic analysis and forecasting of mid-long term load based on spatial autoregressive model[J]. Journal of Northeast Electric Power University, 2021, 41(3): 118–123
[24] 张明慧, 李存斌. 基于逐步回归-灰色预测的中长期电力需求预测[J]. 科技风, 2020(19): 155, 162
[25] 刘青, 张莉莉, 李江涛, 等. “十四五”期间中国电力需求增长趋势研判[J]. 中国电力, 2022, 55(1): 214–219
LIU Qing, ZHANG Lili, LI Jiangtao, et al. Study on the trend of China’s electricity consumption during the “14 th Five Year Plan”[J]. Electric Power, 2022, 55(1): 214–219
[26] 张成龙, 谭显东, 翁玉艳, 等. “十三五”以来电力消费增长原因分析及中长期展望[J]. 中国电力, 2019, 52(8): 149–156
ZHANG Chenglong, TAN Xiandong, WENG Yuyan, et al. Research on the reasons of the growth of electricity consumption during the 13 th Five-year Plan period and medium-and long-term perspective[J]. Electric Power, 2019, 52(8): 149–156

新形势下“十四五”后三年中国电力需求形势研判

Analysis of China’s Power Demand Situation in the Last Three Years of the “14th Five-Year Plan” Under the New Situation

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新形势下“十四五”后三年中国电力需求形势研判

Analysis of China’s Power Demand Situation in the Last Three Years of the “14th Five-Year Plan” Under the New Situation

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