
1.北京工业大学经济与管理学院,北京 100124
2.国网上海市电力公司科技创新部,上海 200122
Received:18 December 2023,
Revised:2024-01-15,
Published:28 February 2024
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李欣,王艳,高宁,等.面向新型电力系统的颠覆性技术识别研究现状与展望[J].新型电力系统,2024,02(1):78-93.
LI Xin,WANG Yan,GAO Ning,et al.Research Status and Prospects of Disruptive Technology Identification for New Power Systems[J].New Type Power Systems,2024,02(01):78-93.
李欣,王艳,高宁,等.面向新型电力系统的颠覆性技术识别研究现状与展望[J].新型电力系统,2024,02(1):78-93. DOI: 10.20121/j.2097-2784.ntps.230048.
LI Xin,WANG Yan,GAO Ning,et al.Research Status and Prospects of Disruptive Technology Identification for New Power Systems[J].New Type Power Systems,2024,02(01):78-93. DOI: 10.20121/j.2097-2784.ntps.230048.
颠覆性技术对新型电力系统结构形态和深度脱碳具有重大颠覆性影响。尽早识别出新型电力系统中的颠覆性技术,对于新型电力系统建设决策和政府能源电力战略决策是至关重要的。为把握新型电力系统颠覆性技术识别研究现状,首先对颠覆性技术识别研究相关文献进行分析,并对比分析国内外颠覆性技术识别研究现状;其次,系统梳理现有颠覆性技术识别方法,并归纳总结各种识别方法的优势、不足及适用条件;最后,分析了现有研究存在的问题,并提出面向新型电力系统建设的颠覆性技术识别研究方向:加强新型电力系统颠覆性技术相关理论研究;将多源数据融合纳入到新型电力系统颠覆性技术识别研究中;将机器学习、深度学习等人工智能方法纳入新型电力系统颠覆性技术的事前识别研究;积极开展新型电力系统不同环节的颠覆性技术识别研究。
Disruptive technologies have a major disruptive impact on the new power system structure and deep decarbonization. It is crucial for new power system construction decisions and government energy power strategic decisions to identify disruptive technologies in new power systems as early as possible. To grasp the research status of disruptive technology identification for new power systems
this paper firstly analyzed the relevant literature on disruptive technology identification research and compared the research status of disruptive technology identification at home and abroad. Second
this paper systematically sorted out the existing disruptive technology identification methods
and summarized the advantages and disadvantages
and applicable conditions of each identification method. Finally
we analyzed the problems of existing research and proposed future research directions for new power systems. In the future
it should strengthen theoretical research on disruptive technologies related to new power systems; incorporate multi-source data fusion into research on identifying disruptive technologies in new power systems; incorporate artificial intelligence methods such as machine learning and deep learning into the research of ex ante identification of disruptive technologies in new power systems
and actively carry out research on disruptive technology identification for new power systems based on different subdivisions.
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