| LONG Huan Title: Lecturer Research directions: Data mining and computational intelligence applied in modeling, optimizing, monitoring the renewable energy and grid system Email: longhuan716@gmail.com, hlong@seu.edu.cn office phone: +86 15195988790 |
Biography：
Dr. LONG Huan was born in Hubei, China in 1992. She received her B.Eng. degree from School of Automation, Huazhong University of Science & Technology, Hubei, China in 2013. She obtained her Ph.D. degree from City University of Hong Kong, Hong Kong in 2017. In 2016, she, as the visiting scholar, went to the intelligent systems laboratory, the University of Iowa, USA. She is currently a lecturer in the School of Electrical Engineering, Southeast University. Her research interests include data mining and computational intelligence applied in modeling, optimizing, monitoring the renewable energy and grid system.
Publications：
Journal
[1] H. Long and Z. Zhang (2017). “Formulation and analysis of grid and coordinate models for planning wind farm layouts,” IEEE Access. Vol. 5: 1810-1819.
[2] Y. Jiang, H. Long, Z. Zhang and Z. Song (2017). “Day-ahead prediction of bi-hourly solar radiation with a Markov switch approach,” IEEE Transactions On Sustainable Energy. In press.
[3] Y. Wang, C. Liu, H. Long, Z. Zhang and S. Yang (2017). “Differential evolution with a new-encoding mechanism for optimizing wind farm layout,” IEEE Transactions On Industrial Informatics. In press.
[4] H. Long, Z. Zhang and M. Eghlimi (2016). “Configuration optimization and analysis of a large scale PV/wind system,” IEEE Transactions On Sustainable Energy. Vol. 8: 84-93.
[5] L. Wang, Z. Zhang, H. Long, J. Xu and R. Hua (2016). “Wind turbine gearbox failure identification with deep neural networks,” IEEE Transactions On Industrial Informatics. In press.
[6] H. Long and Z. Zhang (2015). “A two-echelon wind farm layout planning model,” IEEE Transactions On Sustainable Energy. Vol. 6: 863-971.
[7] H. Long, L. Wang, Z. Zhang, Z. Song and J. Xu (2015). “Data-driven wind turbine power generation performance monitoring,” IEEE Transactions On Industrial Electronics. Vol. 62: 6627-6635.
[8] H. Long, Z. Zhang and Y. Su (2014). “Analysis of daily solar power prediction with data-driven approaches,” Applied Energy. Vol. 126: 29-37.
Conference
[9] H. Long, L. Wang and Z. Zhang (2016). “Wind turbine gearbox failure monitoring based on SCADA data analysis,” 2016 IEEE Power & Energy Society General Meeting, PES. Boston, USA, July. 17-21.
Research：
2014 – 2016, project “robust scheduling of wind farm power generation considering system reliability”, France/Hong Kong joint research scheme, Hong Kong.
2014 – 2015, project “wind turbine performance profile monitoring”, China Longyuan Power Group Corporation Ltd., Beijing, China.
2014 – 2015, project “scheduling power production of hybrid power systems with data mining and computational intelligence”, General research fund, University grand committee, Hong Kong.
