Journal of Zhejiang University

Journal of Zhejiang University SCIENCE A 2026 Vol.27 No.8 P.779-782

Artificial intelligence for carbon neutrality: pioneering a new paradigm for future energy systems research

Author(s): Xiaojie LIN,Jian LI,Rui JING,Zuming LIU,Bowen WANG,Peng LI,Chang HUANG
Affiliation(s): 1. College of Energy Engineering, Zhejiang University, Hangzhou 310027, China more
Corresponding email(s): xiaojie.lin@zju.edu.cn
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Xiaojie LIN, Jian LI, Rui JING, Zuming LIU, Bowen WANG, Peng LI, Chang HUANG. Artificial intelligence for carbon neutrality: pioneering a new paradigm for future energy systems research[J]. Journal of Zhejiang University Science A, 2026, 27(8): 779-782.

@article{title="Artificial intelligence for carbon neutrality: pioneering a new paradigm for future energy systems research",
author="Xiaojie LIN, Jian LI, Rui JING, Zuming LIU, Bowen WANG, Peng LI, Chang HUANG",
journal="Journal of Zhejiang University Science A",
volume="27",
number="8",
pages="779-782",
year="2026",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A26ED001"
}

%0 Journal Article
%T Artificial intelligence for carbon neutrality: pioneering a new paradigm for future energy systems research
%A Xiaojie LIN
%A Jian LI
%A Rui JING
%A Zuming LIU
%A Bowen WANG
%A Peng LI
%A Chang HUANG
%J Journal of Zhejiang University SCIENCE A
%V 27
%N 8
%P 779-782
%@ 1673-565X
%D 2026
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A26ED001

TY - JOUR
T1 - Artificial intelligence for carbon neutrality: pioneering a new paradigm for future energy systems research
A1 - Xiaojie LIN
A1 - Jian LI
A1 - Rui JING
A1 - Zuming LIU
A1 - Bowen WANG
A1 - Peng LI
A1 - Chang HUANG
J0 - Journal of Zhejiang University Science A
VL - 27
IS - 8
SP - 779
EP - 782
%@ 1673-565X
Y1 - 2026
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.A26ED001

Abstract
Chinese Summary
Academic Network
Reviewer Comment

Abstract:

人工智能助力碳中和：开创未来能源系统研究

作者：林小杰¹，李健²，景锐³，刘祖明⁴，王博文⁵，李鹏⁶，黄畅⁷
机构：¹浙江大学，能源工程学院，中国杭州，310027；²北京理工大学，机械与车辆学院，中国北京，100081；³厦门大学，能源学院，中国厦门，361102；⁴上海交通大学，智慧能源创新学院，中国上海，200240；⁵天津大学，机械工程学院，中国天津，300354；⁶华北电力大学（保定），动力工程系，中国保定，071003；⁷暨南大学，国际能源学院，中国珠海，519070
概要：碳中和目标正在推动现代能源系统由集中、单一和确定的运行模式向分布式、多能耦合和高度不确定的形态加速演进。风能、光伏、储能、氢能及供热网络的大规模发展对能源系统的预测、规划、调度、控制和全生命周期管理提出了更高要求。人工智能可通过数据驱动预测、物理信息学习、强化学习、智能优化、数字孪生和生成式模型加快高保真模拟，提升可再生能源预测与消纳能力，促进电-热-气-氢协同调度，并服务于设备设计、故障诊断、材料发现、碳核算和排放监测。本专辑聚焦人工智能与低碳能源工程的深度融合，强调将物理机理、不确定性量化、安全约束和可解释决策嵌入智能方法，推动能源研究由黑箱预测迈向可信决策、由单一设备优化迈向系统与全生命周期协同。未来需进一步解决数据共享、模型泛化、网络安全、隐私保护及工程验证等问题，为构建安全、经济、韧性和可验证低碳的未来能源系统提供科学依据与技术支撑。

关键词：人工智能；碳中和；未来能源系统；多能协同

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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