Fang Shi PhD in Engineering,  Associate Professor, Master’s Supervisor at the School of Electrical Engineering, Shandong University. 

He is an IEEE Member and a Senior Member of both the Chinese Society for Electrical Engineering and the China Electrotechnical Society. 

His research focuses on power system synchrophasor measurement technologies and applications, distribution network fault detection and localization, and artificial intelligence applications in power systems.

He serves as a Standing Committee Member of the IEEE PES (China) Subcommittee on Distribution Network Protection and Control Technology, the Subcommittee on Power System Stability and Control, 

and is a member of the IEC/SC8C WG3 working group. He has led over 20 national and industry research projects, including the National Natural Science Foundation of China and sub-projects under the National Key R&D Program. 

He has published 80+ SCI/EI-indexed papers and holds 20+ authorized invention patents.

Research Team: Advanced Power System Wideband Awareness and Stability Control (AWACS)

Research Interests:

Intelligent distribution network fault diagnosis and localization

AI applications in power system stability analysis and disturbance identification

Power system synchrophasor measurement technologies and applications

Programs: Academic/Professional Master’s students (2–3 per year) in Power System and Automation (Electrical Engineering).

Advantages: Supervisor group-based mentoring, tailored to research interests, emphasizing independent research capabilities.

Support: Generous research assistantships based on project involvement and academic output; funding for academic conferences and exchange programs.

Requirements: Motivated candidates with strong teamwork skills and a passion for research are warmly welcomed.

Publications:

[1]. Zhang H, Shi F, Liu Y, Terzija V. Adaptive online disturbance location considering anisotropy of frequency propagation speeds[J]. IEEE Transactions on Power Systems, 2015, 31(2): 931-941.

[2]. Zhang H, Shi F, Liu Y. Enhancing optimal excitation control by adaptive fuzzy logic rules[J]. International Journal of Electrical Power & Energy Systems, 2014, 63226-235.

[3]. Xie W, Wang X, Fang C, Zhang H, Shi F, Xing X, Sun B. Field experiment using transient energy method to locate a single-phase to ground fault[J]. Global Energy Interconnection, 2020, 3(6): 585-594.

[4]. Wei M, Zhang H, Shi F, Chen W, Terzija V. Nonlinearity characteristic of high impedance fault at resonant distribution networks: Theoretical basis to identify the faulty feeder[J]. IEEE Transactions on Power Delivery, 2021, 37(2): 923-936.

[5]. Wei M, Shi F, Zhang H, Yang F, Chen W. A high-efficiency method to determine parameters of high impedance arc fault models[J]. IEEE Transactions on Power Delivery, 2021, 37(2): 1203-1214.

[6]. Wei M, Shi F, Zhang H, Jin Z, Terzija V, Zhou J, Bao H. High impedance arc fault detection based on the harmonic randomness and waveform distortion in the distribution system[J]. IEEE transactions on power delivery, 2019, 35(2): 837-850.

[7]. Wei M, Shi F, Zhang H, Chen W. Wideband synchronous measurement-based detection and location of high impedance fault for resonant distribution systems with integration of DERs[J]. IEEE Transactions on Smart Grid, 2022, 14(2): 1117-1134.

[8]. Wei M, Liu W, Zhang H, Shi F, Chen W. Distortion-based detection of high impedance fault in distribution systems[J]. IEEE Transactions on power delivery, 2020, 36(3): 1603-1618.

[9]. Wei M, Liu W, Shi F, Zhang H, Jin Z, Chen W. Distortion-controllable arc modeling for high impedance arc fault in the distribution network[J]. IEEE Transactions on Power Delivery, 2020, 36(1): 52-63.

[10]. Wang X, Zhang H, Shi F, Wu Q, Terzija V, Xie W, Fang C. Location of single phase to ground faults in distribution networks based on synchronous transients energy analysis[J]. IEEE Transactions on Smart Grid, 2019, 11(1): 774-785.

[11]. Wang X, Wang P, Wang Y, Shi F. Online estimation of short-circuit fault level in active distribution network[J]. Applied Sciences, 2020, 10(11): 3812.

[12]. Sun Y, Li S, Xu Q, Xie X, Jin Z, Shi F, Zhang H. Harmonic contribution evaluation based on the distribution-level PMUs[J]. IEEE Transactions on Power Delivery, 2020, 36(2): 909-919.

[13]. Song F, Mehedi H, Liang C, Meng J, Chen Z, Shi F. Review of transition paths for coal-fired power plants[J]. Global Energy Interconnection, 2021, 4(4): 354-370.

[14]. Shi F, Zhang L, Zhang H, Xu K, Vladimir T. Diagnosis of the single phase‐to‐ground fault in distribution network based on feature extraction and transformation from the waveforms[J]. IET Generation, Transmission & Distribution, 2020, 14(25): 6079-6086.

[15]. Shi F, Zhang H, Xue G. Instability prediction of the inter-connected power grids based on rotor angle measurement[J]. International Journal of Electrical Power & Energy Systems, 2017, 8821-32.

[16]. Mehedi H, Wang X, Ye S, Xue G, Shariful I M, Shi F. Power generation expansion planning approach considering carbon emission constraints[J]. Global Energy Interconnection, 2023, 6(2): 127-140.

[17]. Liu C, Ma H, Zhang H, Shi X, Shi F. A MILP-based battery degradation model for economic scheduling of power system[J]. IEEE Transactions on Sustainable Energy, 2022, 14(2): 1000-1009.

[18]. Jin Z, Zhang H, Shi F, Sun Y, Terzija V. A robust and adaptive detection scheme for interharmonics in active distribution network[J]. IEEE Transactions on power delivery, 2018, 33(5): 2524-2534.

[19]. Hasan M M, Shi F, Zhang H, Liu Z, Vladimir T, Shi X. Review of model-driven and data-driven/AI approaches for estimating frequency dynamics after a disturbance[J]. Renewable and Sustainable Energy Reviews, 2026, 226116225.

Contact: shifang@sdu.edu.cn