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Dr Lurui Fang is currently an Assistant Professor in the Department of Electrical and Electronics Engineering, School of Advanced Technology at Xi'an Jiaotong-Liverpool-Liverpool University (XJTLU).

Dr Fang obtained Ph.D. degree from the University of Bath in 2021. Before that, he was a research and field engineer in Chongqing Datang International Pengshui Hydro Power Ltd, 2015-2017.

Dr Fang's research interests are within developing new analysis tools for power system planning and diagnosis, alongside new economic theories for future power systems. His research currently has two focuses: 1) tangible network and generation expansion strategies for future power systems; 2) Carbon accounting, tracing and net-zero pathway design for power systems.

Accepting PhD students and RAs.

Qualifications
- Ph.D. University of Bath, - 2021
- M.Sc., University of Southampton, -2014
Experience
- Lecturer - Xi'an Jiaotong-Liverpool University, 2021-Present
- Group Assistant, Centre for Sustainable Power Distribution, University of Bath, 2019-2021
- Research and Field Engineer, Chongqing Datang International Pengshui Hydro Power Ltd, 2015-2017
Research interests
- Machine-learning applications on power systems
- Low-carbon power system planning
- Power system economics
Articles
- Mohammad Yazdani-Asrami*, Lurui Fang*, Xiaoze Pei and Wenjuan Song, "Smart fault detection of HTS coils using artificial intelligence techniques for large-scale superconducting electric transport applications", in Superconductor Science and Technology, Vol. 36, no 8, doi: 10.1088/1361-6668/ace3fb
- J. li, X. Wei, L. Fang*, Y. Zhu, C. Gu, Y. Xiang, “Short-Term Load Forecasting Facilitated by Edge Data Centres: A Coordinated Edge-Cloud Approach”, IEEE Transactions on Smart Grid, submitted
- Xiaoyang Chen, Yang Du, Enggee Lim, Lurui Fang, Ke Yan, Towards the applicability of solar nowcasting: A practice on predictive PV power ramp-rate control, Renewable Energy, Volume 195, 2022, Pages 147-166,
- L. Fang, K. Ma, F. Li and F. Xue, "Novel Incentive Scheme to Motivate Flexible Customers for Phase Balancing," in CSEE Journal of Power and Energy Systems, vol. 8, no. 4, pp. 1048-1059, July 2022, doi: 10.17775/CSEEJPES.2021.07810.
- S. Cheng, C. Gu, X. Yang, S. Li, L. Fang and F. Li, "Network Pricing for Multienergy Systems Under Long-Term Load Growth Uncertainty," in IEEE Transactions on Smart Grid, vol. 13, no. 4, pp. 2715-2729, July 2022, doi: 10.1109/TSG.2022.3159647.
- Sun Qixing (孙启星)，Xing Dong (邢栋)，Zhang Chao (张超)，Fang Luru (方鲁睿 )*， You Peipei (尤培培)，Li Sitao (李司陶), "Trans-provincial Clearing Mechanism for Capacity Market in China (适应中国背景的跨省区容量市场联合出清机制)", in Proceedings of the CSU-EPSA (电力系统及其自动化学报), 2022, doi: 10.19635/j.cnki.csu-epsa.000961.
- L. Fang, K. Ma, and Z. Zhong, ” A Statistical Methodology to identify Imbalance-Induced Capacity Wastes for LV Networks”, in Electric Power System Research, in Electric Power System Research, Vol. 199, Oct. 2021, doi: 10.1016/j.epsr.2021.107388.
- H. Wu, Y. Yuan, K. Ma and L. Fang, "Estimate the Probability Distribution of Imbalance-Induced Energy Loss With Minimal Data," in IEEE Transactions on Power Systems, vol. 36, no. 4, pp. 3798-3801, July 2021, doi: 10.1109/TPWRS.2021.3062217.
- K. Ma, L. Fang and W. Kong, “Review of distribution network phase unbalance: Scale, causes, consequences, solutions, and future research directions,” in CSEE Journal of Power and Energy Systems, vol. 6, no. 3, pp. 479-488, Sept. 2020, doi: 10.17775/CSEEJPES.2019.03280.
- W. Kong, K. Ma, L. Fang, R. Wei and F. Li, "Cost-Benefit Analysis of Phase Balancing Solution for Data-Scarce LV Networks by Cluster-Wise Gaussian Process Regression," in IEEE Transactions on Power Systems, vol. 35, no. 4, pp. 3170-3180, July 2020, doi: 10.1109/TPWRS.2020.2966601.
- L. Fang and K. Ma, “Assessment of additional phase energy losses caused by phase imbalance for datascarce LV networks,” in IET Generation, Transmission & Distribution, vol. 14, no. 4, pp. 675-681, Feb. 2020, doi: 10.1049/iet-gtd.2019.1036.4.
- L. Fang, K. Ma and X. Zhang, “A Statistical Approach to Guide Phase Swapping for Data-Scarce Low Voltage Networks,” in IEEE Transactions on Power Systems vol. 35, no. 1, pp. 751-761, Jan. 2020, doi: 10.1109/TPWRS.2019.2931981.
- L. Fang, K. Ma, R. Li, Z. Wang and H. Shi, “A Statistical Approach to Estimate Imbalance-Induced Energy Losses for Data-Scarce Low Voltage Networks,” in IEEE Transactions on Power Systems vol. 34, no. 4, pp. 2825-2835, July 2019, doi: 10.1109/TPWRS.2019.2891963.
Grants
- Lurui Fang, PI, Research on using situation awareness and transfer learning for fault prediction of wind turbines, External Funding (Industrial Collaboration), 2022 July (RMB 500k)
- Lurui Fang, PI, Research on the impact of physical characteristics of cables to distribution system investments and operation costs, Research Development Fund (RDF), Xi’an Jiaotong-Liverpool University, China, 2022 Sep (RMB 87.6k)
Courses taught
- EEE421, Integration of Energy Strategies in the Design of Buildings, Number of students enrolled: 44(2022)
- EEE210, Energy Conversion and Power Systems, Number of students enrolled: 144(2022)
- EEE104, Digital Electronics I, Number of students enrolled: 581(2022)
Professional memberships
- Member, CSEE
- Member, IET
- Member, IEEE
Awards and honours
- "Class B" for School-enterprise Advisor Exchange - SuZhou Industry Park - 2022

电话
+86 (0)51288161841
Email
Lurui.Fang@xjtlu.edu.cn
地址
SC471(SIP Campus-Science Building)
Suzhou Dushu Lake Science and Education Innovation District
Suzhou Industrial Park
Suzhou
P.R.China
215123

Lurui FangPh.D.

Profile

Qualifications

Experience

Research interests

Articles

Grants

Courses taught

Professional memberships

Awards and honours