Prof. Miao He

Department of Electrical and Computer Engineering,

Texas Tech University, USA.

Email: miao.he@asu.edu

Qualifications

2013  Ph.D., Arizona State University, USA

2008  M.Sc., Tsinghua University, China

2005  B.Sc., Nanjing Univ. of Posts & Telecom, China

Publications (selected)

1. M. He and J. Zhang, “A Dependency Graph Approach for Fault Detection and Localization Towards Secure Smart Grid,” IEEE Transactions on Smart Grid, vol.2, no.2, pp.342-351, June 2011.
2. M. He, S. Murugesan and J. Zhang, “A Multi-timescale Scheduling Approach for Stochastic Reliability in Smart Grids with Integrated Wind Generation and Opportunistic Demand,” IEEE Transactions on Smart Grid, vol.4, no.1, pp.521-529, Mar 2013.
3. M. He, V. Vittal and J. Zhang, “Online Dynamic Security Assessment of Power Systems with Missing PMU Measure- ments: A Data Mining Approach,” IEEE Transactions on Power Systems, vol.28, no.2, pp.1969-1977, May 2013.
4. M. He, J. Zhang and V. Vittal, “Robust On-line Dynamic Security Assessment using Adaptive Ensemble Decision Tree Learning,” IEEE Transactions on Power Systems, vol.28, no.4, pp.4089-4098, Nov 2013.
5. M. He, L. Yang, J. Zhang and V. Vittal, “A Spatio-temporal Analysis Approach for Short-term Wind Farm Generation Forecast,” IEEE Transactions on Power Systems, vol.29, no.4, pp.1611-1622, July 2014.
6. L. Yang, M. He, J. Zhang, and V. Vittal, Spatio-Temporal Data Analytics for Wind Energy Integration, Springer, 2014.
7. S. Abedi and M. He, “Alternate Energy Sources,” in Handbook of Electric Power Calculation, McGraw-Hill, 2015.
8. L. Yang, M. He, J. Zhang and V. Vittal, “Support-Vector-Machine-Enhanced Markov Model for Short-Term Wind Power Forecast”, IEEE Transactions on Sustainable Energy, vol.6, no.3, pp.791-799, July 2015.
9. R. Kumar, M. Giesselmann, S. Bayne and M. He, “Generalized Method for Formulation of Optimal PMU Placement Problem,” Int’l Journal of Power and Energy Systems, vol.35, pp.1710-2243, 2015.
10. Y. Cao, T. Jiang, M. He and J. Zhang, “Device-to-Device Communications for Energy Management: A Smart Grid Case” in IEEE Journal on Selected Areas in Communications, vol.34, no.1, pp190-201, Jan 2016.
11. L. Yang, M. He, V. Vittal and J. Zhang, “Stochastic Optimization based Economic Dispatch and Interruptible Load Management with Increased Wind Penetration”, IEEE Transactions on Smart Grid, vol.7, no.2, pp.730-739, Mar 2016.
12. R. Kumar, M. Giesselmann, S. Bayne and M. He, “State and Parameter Estimation of Power Systems using Phasor Measurement Units as Bilinear System Model”, Int’l Journal of Renewable Energy Research, vol.6, no.4, pp. 1373-1384, Dec 2016.
13. J. Zhao, S. Abedi, M. He, P. Du, S. Sharma and B. Blevins, “Quantifying Risk of Wind Power Ramps in ERCORT” IEEE Transaction on Power Systems, nol.32, no.4, pp. 4970-4971, Nov 2017.
14. S. Abedi, M. He, and D. Obadina, “Congestion Risk-aware Unit Commitment with Signi?0?3cant Wind Power Generation, IEEE Transaction on Power Systems, vol.33, no.6, 6861-6869, Nov 2018.
15. X. Chen, I. Zaman, and M. He, “Pattern Detection, Mapping, and Visualization of Wind Ramp Events using Real-time Mesoscale Weather Measurements,” to appear, Elsevier Energy and AI.
16. S. Dinkhah and M. He, “Reinforcement Learning-based Hybrid V2G Control for Microgrid Applications,” accepted, Elsevier Energy and AI.

Profile Details

https://www.depts.ttu.edu/ece/faculty/miao_he/index.php

http://scholar.google.com/citations?user=CKEUxPgAAAAJ&hl=zh-CN