系所与团队：

电力系统研究所

电力系统经济运行团队

山东省数字智慧能源创新重点实验室

学术身份：

1. 教授、博士生导师，山东省数字智慧能源创新重点实验室副主任

2. 国家自然科学联合基金（重点）项目负责人；中国工程院“中国工程前沿杰出青年学者”；中国科协“青年人才托举工程”入选者；首届山东省优秀青年科学基金（海外）获得者；入选斯坦福&爱思唯尔全球前2%顶尖科学家榜单

3. 《IEEE Transactions on Power Delivery》、《CAAI Transactions on Intelligence Technology》、《Protection and Control of Modern Power Systems》、《CSEE Journal of Power and Energy Systems》、《IET Renewable Power Generation》编委；《电力自动化设备》、《中国电力》青年编委；多个国内外专刊特约编辑

4. IEEE PES输配电技术委员会秘书；中国电机工程学会区块链专委会委员；中国电工技术学会主动配电网及分布式电源专委会委员；中国能源研究会电能技术专委会委员；山东省国家知识产权保护中心人才专家

5. IEEE/IET等多个国际会议的会议主席/程序委员会主席/出版主席/分会主席/特邀报告；Nature子刊等十余个国内外顶级期刊审稿人

6. 国际注册工程师（CEng）；IEEE Senior Member；中国电机工程学会/中国电工技术学会高级会员

主要工作经历：

2025至今，山东省数字智慧能源创新重点实验室 副主任

2020至今，伟德国际bv1946 教授

2020至今，美国哈佛大学（Harvard University） 客座研究员

2018-2020，美国哈佛大学（Harvard University） 博士后

2016-2017，美国德州大学阿灵顿分校/爱荷华州立大学/南卫理公会大学（The University of Texas at Arlington/Iowa State University/Southern Methodist University） 访问学者

2015，北京ABB有限公司 项目工程师

2013-2018，上海交通大学 电气工程 博士

2016-2018，美国佐治亚理工公司（Georgia Institute of Technology） 计算机科学 硕士

2009-2013，伟德国际bv1946 电气工程 学士

研究方向：

电力系统运行优化与智能感知，智能配电分层调控，可再生能源并网，电力市场，能源经济与政策

学术著作：

录用/发表包括一作Nature Communications/Nature Geoscience在内的SCI/EI论文100余篇，入选ESI高被引/热点论文10余篇次，出版一作、编委专著3部，授权国内/国际专利20余项（美国专利2项），主编1项国际标准，参编1 项国家标准。每年部分成果如下（*为通讯作者）：

1. 专著

[1]Tianguang Lu, M. Yang, Y. Guo, Q. Ai, R. Hao. “Operation modeling and collaborative regulation of distributed energy grid clusters.” Springer, 2025.

[2]吕天光，艾芊. “微电网群分层调控技术.” 上海科学技术出版社,2022.

2. 期刊论文

[1] J. Liang, S.Wu,Tianguang Lu*.“Portfolio selection and optimal planning for hydrogen energy storage systems composed of heterogeneous electrolyzer and fuel cell technologies in industrial park multi-energy systems.” Applied Energy, 2026.（发表，SCI，ESI热点，IF：11）

[2]Tianguang Lu*, Y. Guo,X. Chen, C. P. Nielsen, M. B. McElroy. “Economic behaviors of generation companies at higher penetration of renewables under different market concentrations.” Journal of Cleaner Production, 2026.（发表，SCI，IF：9.8）

[3] S. Wu,Tianguang Lu*. “Cascade Feedforward Neural Network based Deep Greedy Search: An Efficient MPPT Strategy for Proton Exchange Membrane Fuel Cell System.” Energy,2026.（在线发表，SCI，IF：9）

[4] Y.Zhang,Tianguang Lu*, L. Zhang, Y. Mei, Y. Guo, S. Wu, Q. Wu, Y. Xu. “Low-carbon optimal dispatching of rural multi-energy microgrid system based on multi-energy conversion and agricultural load demands.” Energy,2026.（发表，SCI，IF：9）

[5] H. Zeng, Y. Guo, Y. Xu,Tianguang Lu*.“Siting and sizing planning for multi-type energy replenishment stations in urban traffic network considering mixed traffic flow.” Sustainable Energy, Grids and Networks, 2026.（发表，SCI，IF: 5.6）

[6] Y. Guo,TianguangLu*, H. Zeng, Y. Zhang, Q. Ai. “Energy-efficient scheduling of low-carbon heterogeneous energy-integrated virtual power plants with 5G base station energy storage participation.”International Journal of Electrical Power & Energy Systems, 2025.（发表，SCI，IF: 5.6）

[7] X. Yi,Tianguang Lu*, Y. Li, Q. Ai. “Collaborative planning of multi-energy systems integrating complete hydrogen energy chain.” Renewable and Sustainable Energy Reviews, 2025. （发表，SCI，ESI热点，IF：16.3）

[8]Tianguang Lu*, X. Yi, J. Li, S. Wu. “Collaborative planning of integrated hydrogen energy chain multi-energy systems: A review.” Applied energy, 2025.（发表，SCI，ESI高被引，IF：11）

[9] H. Liu,Tianguang Lu*, Y. Yang, Y. Guo, Q. Wu, X. Xu, H. Zeng. “Blockchain-based optimization of operation and trading among multiple microgrids considering market fairness.” International Journal of Electrical Power & Energy Systems, 2025. （发表，SCI，ESI高被引，IF：5）

[10] 吴钦政，吕天光*，刘卫东，高扬，武少聪，张宇昊，郭宇. “机理-数据融合驱动的变压器匝间故障诊断研究.” 中国电机工程学报, 2025.（发表，EI）

[11] E. Yaghoubi, E. Yaghoubi, A. Khamees, D. Razmi,Tianguang Lu*. “A systematic review and meta-analysis of machine learning, deep learning, and ensemble learning approaches in predicting EV charging behavior.” Engineering Applications of Artificial Intelligence, 2024.（发表，SCI，IF：8）

[12] J. Li,Tianguang Lu*, X. Yi, R. Hao, Q. Ai, Y. Guo, M. An, S. Wang, X. He, Y. Li. “Concentrated solar power for a reliable expansion of energy systems with high renewable penetration considering seasonal balance.” Renewable Energy, 2024.（发表，SCI，ESI高被引，ESI热点，IF：9.1）

[13] J. Li,Tianguang Lu*, X. Yi, M. An, R. Hao. “Energy systems capacity planning under high renewable penetration considering concentrating solar power.” Sustainable Energy Technologies and Assessments, 2024.（发表，SCI，ESI高被引，ESI热点，IF：7）

[14] H. Cheng,Tianguang Lu*, R. Hao, J. Li, Q. Ai. “Incentive-based demand response optimization method based on federated learning with a focus on user privacy protection.” Applied Energy, 2024.（发表，SCI，IF：11）

[15] S. Wang,Tianguang Lu*, R. Hao, F. Wang, T. Ding, J. Li, X. He, Y. Guo, X. Han. “An Identification Method for Anomaly Types of Active Distribution Network Based on Data Mining.” IEEE Transactions on Power Systems, 2023.（发表，SCI，ESI高被引，ESI热点，IF：7.2）

[16] D. Razmi,Tianguang Lu*, B. Papari, E. Akbari, G. Fathi and M. Ghadamyari. “An overview on power quality issues and control strategies for distribution networks with the pres ence of distributed generation resources.” IEEE Access, 2023.（发表，SCI，IF：3.6）

[17]Tianguang Lu, X. Chen, M. B. McElroy, C. P. Nielsen, Q. Wu, H. He, and Q. Ai. “A reinforcement learning-based decision system for electricity pricing plan selection by smart grid end users.” IEEE Transactions on Smart Grid，2022. （发表，SCI，IF：9.8）

[18]Tianguang Lu*, R. Hao, Q. Ai, and H. He. “Distributed online dispatch for microgrids using hierarchical reinforcement learning embedded with operation knowledge.” IEEE Transactions on Power Systems，2022. （发表，IF：7.2）

[29] R. Hao,Tianguang Lu*, Q. Ai, H. He. “Data-oriented distributed demand response optimization with global inequality constraints based on multi-agent system.” International Journal of Electrical Power & Energy Systems, 2021.（发表，SCI，IF：5）

[20]Tianguang Lu, P. Sherman, X. Chen, S. Chen, X. Lu, and M. B. McElroy. “India’s potential for integrating solar and on- and offshore wind power into its energy system.”Nature Communications, 2020. （发表，nature子刊，IF：15.7）

[21] R. Hao,Tianguang Lu*, and Q. Ai. “Distributed online learning and dynamic robust standby dispatch for networked microgrids.” Applied Energy, 2020.（发表，SCI，IF：11）

[22] F. Xiao,Tianguang Lu*, Q. Ai, X. Wang, X. Chen, S. Fang, and Q. Wu. “Design and implementation of a data-driven approach to visualizing power quality.” IEEE Transactions on Smart Grid, 2020.（发表，SCI，IF：9.8）

[23] S. Yin, Q. Ai, Z. Li, Y. Zhang, and Tianguang Lu*. “Energy management for aggregate prosumers in a virtual power plant: A robust Stackelberg game approach.” International Journal of Electrical Power & Energy Systems, 2020.（发表，SCI，IF：5）

[24]Tianguang Lu, Z. Wang, J. Wang, Q. Ai, and C. Wang. “A data-driven stackelberg market strategy for demand response-enabled distribution systems.” IEEE Transactions on Smart Grid, 2019.（发表，SCI，IF：9.8）

[25] R. Hao,Tianguang Lu*, Q. Wu, X. Chen, and Q. Ai. “Distributed piecewise approximation economic dispatch for regional power systems under non-ideal communication.” IEEE Access, 2019.（发表，SCI，IF：3.6）

[26] Y. Zhang, Q. Ai, F. Xiao, R. Hao, and Tianguang Lu*. “Typical wind power scenario generation for multiple wind farms using conditional improved Wasserstein generative adversarial network.” International Journal of Electrical Power & Energy Systems, 2019.（发表，SCI，IF：5）

[27] F. Xiao,Tianguang Lu, M. Wu, and Q. Ai. “Maximal overlap discrete wavelet transform and deep learning for robust denoising and detection of power quality disturbance.” IET Generation Transmission & Distribution, 2019.（发表，SCI，IF：2.6）

[28] F. Shen, J. C. López, Q. Wu, M. J. Rider,Tianguang Lu, N. D. Hatziargyriou. “Distributed self-healing scheme for unbalanced electrical distribution systems based on alternating direction method of multipliers.” IEEE Transactions on Power Systems, 2019.（发表，SCI，IF：7.2）

[29] H. He, D. Luo, W. Lee, Z. Zhang, Y. Cao, and Tianguang Lu. “A contactless insulator contamination levels detecting method based on infrared images features and RBFNN.” IEEE Transactions on Industry Applications, 2019.（发表，SCI，IF：4.5）

[30]Tianguang Lu*, Q. Ai, and Z. Wang. “Interactive game vector: A stochastic operation-based pricing mechanism for smart distribution systems with coupled-microgrid.” Applied Energy, 2018.（发表，SCI，IF：11）

[31]Tianguang Lu, W. Lee, Q. Ai, and S. Lu. “A priority decision making-based biding strategy for interactive aggregators.” IEEE Transactions on Industry Applications, 2018.（发表，SCI，IF：4.5）

[32]Tianguang Lu*, Z. Wang, Q. Ai, and W. Lee. “Interactive model for energy management of clustered microgrids.” IEEE Transactions on Industry Applications, 2017.（发表，SCI，IF：4.5）

[33]Tianguang Lv* and Q. Ai. “Interactive energy management of networked microgrids-based active distribution system considering large-scale integration of renewable energy resources.” Applied Energy, 2016.（发表，SCI，ESI高被引，IF：11）

[34]Tianguang Lv*, Q. Ai, and Y. Zhao. “A bi-level multi-objective optimal operation of grid-connected microgrids.” Electric Power Systems Research, 2016.（发表，SCI，IF：4.2）

[35] K. Yu, S. Wang, Q. Ai, J. Ni, and Tianguang Lv. “Analysis and optimization of droop controller for microgrid system based on small-signal dynamic model.” IEEE Transactions on Smart Grid, 2016.（发表，SCI，IF：9.8）

[36]吕天光*，艾芊，孙树敏，程艳，赵媛媛. “含多微网的主动配电系统综合优化运行行为分析与建模.” 中国电机工程学报, 2016.（发表，EI）

部分获奖：

2026，PCMP优秀编委

2025，日内瓦国际发明展评审团特别嘉许金奖（排1）

2024，中国工程院“中国工程前沿杰出青年学者”

2024，中国产学研合作创新奖

2023，新疆维吾尔自治区科技进步奖二等奖（排1）

2023，《电机工程学报》优秀审稿专家

2022，中国电力科技创新奖二等奖

2021，中国电力科技创新奖一等奖（排1）

2021，山东电力科学技术进步奖三等奖

2021、2022，《电网技术》优秀审稿专家

2020，山东电机工程学会五四优秀青年科技工作者

2019，IEEE工业应用协会最佳论文奖

2019，上海交通大学优秀博士学位论文

2017，IEEE工业应用协会最佳论文奖

2017，中国电机工程学报年度优秀作者

2014，山东省优秀学位论文

主要科研项目：

[1]. 国家自然基金

[2]. 山东省优秀青年科学基金（海外）

[3]. 中国科协“青年人才托举工程”

[4]. 国网总部科技项目

[5]. 美国能源部研究项目

[6]. China 2030/2050: Energy and Environmental Challenges for the Future，HarvardGlobal Institute

[7]. 伟德国际bv1946“齐鲁青年学者”建设项目

招生类型：

学术型和专业型的硕士/博士研究生。

课题组与国内外著名高校和研究机构具有良好合作关系，关注学科交叉。有志于攻读相关研究方向的硕士/博士研究生以及科研助理/博士后，请邮件联系