
海上风电支撑我国能源转型发展的思考
Offshore Wind Power Supports China’s Energy Transition
我国海上风电资源丰富,且靠近东部沿海经济发达省份,就地消纳优势巨大,发展海上风电有助于加快我国能源转型进程,助力2030 年碳达峰、2060 年碳中和目标的实现。本文在分析我国能源发展现状、趋势和面临挑战的基础上,指出发展海上风电是我国能源结构转型的重要战略支撑。从风电机组、海上输电、海洋工程和运维技术等四个领域归纳提炼了我国海上风电发展的关键技术。针对目前我国海上风电产业发展面临的诸多瓶颈问题,从海上风电资源勘查与评估、提高能源转型认识、宏观统筹与整体规划、科技创新、政策扶持机制等五方面提出了促进我国海上风电产业健康有序发展的对策与建议,以期为我国海上风电高质量发展和政府有关部门决策提供参考。
China is rich in offshore wind power resources, and these resources can be locally consumed by the economically developed provinces located in the eastern coastal region. The development of offshore wind power can accelerate the energy transition in China and help achieve carbon peak in 2030 and carbon neutrality in 2060. In this article, we analyze the current situation, trends, and challenges of energy development in China, and propose that the development of offshore wind power is an important strategic support for the energy structure transformation in China. The key technologies of offshore wind power development in China are summarized including wind turbine, offshore power transmission, offshore engineering, and operation and maintenance technologies. In view of the bottleneck problems restricting the development of China’s offshore wind power industry, we propose some countermeasures and suggestions to promote the healthy and orderly development of China’s offshore wind power industry from five aspects: exploration and evaluation of offshore wind power resources, understanding of energy transition, overall planning and integrated planning, scientific and technological innovation, and policy support mechanism.
energy transition / offshore wind power / key technologies of offshore wind power
[1] |
刘吉臻, 王庆华, 房方, 等. 数据驱动下的智能发电系统应用架 构及关键技术 [J]. 中国电机工程学报, 2019, 39(12): 3578–3587. Liu J Z, Wang Q H, Fang F, et al. Data-driven-based application architecture and technologies of smart power generation [J]. Proceedings of the CSEE, 2019, 39(12): 3578–3587.
|
[2] |
中国政府网. 习近平在第七十五届联合国大会一般性辩论上 发表重要讲话 [EB/OL]. (2020-09-22)[2020-11-20]. http: //www. gov.cn/xinwen/2020-09/22/content_5546168.htm. Chinese Government Network. Xi Jinping delivers an important speech at the general debate of the 75th UN General Assembly. [EB/OL]. (2020-09-22)[2020-11-20]. http: //www.gov.cn/ xinwen/2020-09/22/content_5546168.htm.
|
[3] |
中国政府网. 习近平在气候雄心峰会上发表重要讲话 [EB/OL]. (2020-12-13) [2020-12-15]. http: //www.gov.cn/xinwen /2020- 12/13/content_5569136.htm. Chinese Government Network. Xi Jinping delivers an important speech at the Climate Ambition Summit [EB/OL]. (2020-12- 13) [2020-12-15]. http: //www.gov.cn/xinwen /2020-12/13/ content_5569136.htm.
|
[4] |
国家统计局. 中国统计年鉴2020 [M]. 北京: 中国统计出版社, 2020. National Bureau of Statistics. China statistical yearbook of 2020 [M]. Beijing: China Statistics Press, 2020.
|
[5] |
BP. Statistical review of world energy (2020 edition) [R]. London: BP, 2020.
|
[6] |
易跃春. 中国海上风电2018 [J]. 电力设备管理, 2018 (12): 81– 83. Yi Y C. China offshore wind power 2018 [J]. Electric Power Equipment Management, 2018 (12): 81–83.
|
[7] |
陈玲娜. 海上风电的发展现状和前景分析 [J]. 中国高新科技, 2020 (13): 75–76. Chen L N. Development status and prospect analysis of offshore wind power [J]. China High-Tech, 2020 (13): 75–76.
|
[8] |
张瑞刚, 王冰佳, 王杰彬, 等. 海上风电叶片行业优点及发展阻 碍分析 [J]. 船舶工程, 2020, 42(S1): 523–525. Zhang R G, Wang B J, Wang J B, et al. Advantages and development obstacles of offshore wind turbine blade industry [J]. Ship Engineering, 2020, 42(S1): 523–525.
|
[9] |
张宏伟, 闫瑞志, 薛鹏, 等. 风电机组主轴承的设计与技术要求 [J]. 轴承, 2014 (4): 14–19. Zhang H W, Yan R Z, Xue P, et al. Design and technical requirements of main bearings in wind turbines [J]. Bearing, 2014 (4): 14–19.
|
[10] |
谢鲁冰, 张振华, 武国洪. 直驱与双馈风机技术流派对比分析 [J]. 应用能源技术, 2012 (8): 42–44. Xie L B, Zhang Z H, Wu G H. Technology comparison and analysis of direct driving and double led for the wind power turbine [J]. Applied Energy Technology, 2012 (8): 42–44.
|
[11] |
张开华, 张智伟, 王婧倩, 等. 海上风电场输电系统选择 [J]. 太 阳能, 2019 (2): 56–60, 55. Zhang K H, Zhang Z W, Wang J Q, et al. Offshore wind farm transmission system selection [J]. Solar Energy, 2019 (2): 56–60, 55.
|
[12] |
王锡凡, 卫晓辉, 宁联辉, 等. 海上风电并网与输送方案比较 [J]. 中国电机工程学报, 2014, 34(31): 5459–5466. Wang X F, Wei X H, Ning L H, et al. Integration techniques and transmission schemes for off-shore wind farms [J]. Proceedings of the CSEE, 2014, 34(31): 5459–5466.
|
[13] |
李翔宇, Gayan Abeynayake, 姚良忠, 等. 欧洲海上风电发展现 状及前景 [J]. 全球能源互联网, 2019, 2(2): 116–126. Li X Y, Gayan Abeynayake, Yao L Z, et al. Recent Development and prospect of offshore wind power in Europe [J]. Journal of Global Energy Interconnection, 2019, 2(2): 116–126.
|
[14] |
重磅! 亨通中标葡萄牙海上浮式风电海底高压电缆总包项目 [J]. 现代传输, 2018 (4): 6. Heavy! Hengtong won the bid for Portuguese offshore floating wind power submarine high-voltage cable general contracting project [J]. Modern Transmission, 2018 (4): 6.
|
[15] |
符杨, 郑紫宸, 时帅, 等. 考虑气象相似性与数值天气预报修正 的海上风功率预测 [J]. 电网技术, 2019, 43(4): 1253–1260. Fu Y, Zheng Z C, Shi S, et al. Offshore wind power forecasting considering meteorological similarity and NWP correction [J]. Power System Technology, 2019, 43(4): 1253–1260.
|
[16] |
牛东晓, 赵东来, 杨尚东, 等. 基于改进粒子群算法的海上风 电汇集方式与并网优化研究 [J]. 中南大学学报(自然科学版), 2019, 50(12): 3146–3155. Niu D X, Zhao D L, Yang S D, et al. Research on convergence mode and grid-connected optimization of offshore wind power based on improved particle swarm optimization algorithm [J]. Journal of Central South University (Science and Technology), 2019, 50(12): 3146–3155.
|
[17] |
段慧云, 汪洋青. 人工智能技术在风电机组智能巡检中的应用 [J]. 科学技术创新, 2019 (30): 155–156. Duan H Y, Wang Y Q. Application of artificial intelligence technology in intelligent inspection of wind turbines [J]. Scientific and Technological Innovation, 2019 (30): 155–156.
|
/
〈 |
|
〉 |