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清华大学材料科学与工程研究院《材料科学论坛》:Design and Properties of Hybrid...
清华大学材料科学与工程研究院《材料科学论坛》:Photoalignment for liquid crystals
Pseudo-criticality and its implication for the lost conformality
Implications of superadditive algebras in large N field theories for holography
报告题目:
Data-Driven Multi-Model Blending for Renewable Energy Forecasting
 报告人:
Jie Zhang
Assistant Professor
Department of Mechanical Engineering
Department of Electrical Engineering (by courtesy)
University of Texas at Dallas
报告时间:
2016-12-16 10:00
报告地点:
西主楼3-102
主办单位:
电机系
  简介:

报告人: Jie Zhang
Assistant Professor
Department of Mechanical Engineering
Department of Electrical Engineering (by courtesy)
University of Texas at Dallas

时间:2016年12月16日上午10:00
地  点:西主楼3-102
联系人:胡泽春


报告摘要:
Variable renewable energy resources such as wind and solar power are becoming increasingly important sources of energy on the electric power system.
The consistent growth of renewable energy calls for a paradigm shift in energy systems technologies, aiming to efficiently solve power systems challenges
with large penetrations of renewable energy and energy efficiency technologies. Improving wind and solar forecasting accuracy becomes increasingly
important to ensure economic and reliable operations.
This presentation will discuss several recently developed data-driven methodologies in wind and solar forecasting, including:
 (i) improved wind power forecasting using big data information processing technologies, leading to significant production cost reductions in power system operations;
 (ii) a situation-dependent multi-expert machine learning solar forecasting methodology; and
 (iii) a ramp identification and forecasting method for extreme events.
Both the economic and reliability benefits from improved wind and solar power forecasting will also be discussed.

 

报告人简历:
Dr. Jie Zhang is currently an Assistant Professor in the Department of Mechanical Engineering and (by courtesy) Department of Electrical Engineering at the
University of Texas at Dallas (UTD). Before joining UTD, he was a Research Engineer at the National Renewable Energy Laboratory (NREL). Dr. Zhang received
his Ph.D. (2012) in Mechanical Engineering from Rensselaer Polytechnic Institute (RPI), Troy, NY, USA. He received his B.S. (2006) and M.S. (2008) in Mechanical
Engineering from Huazhong University of Science & Technology, Wuhan, China. His research expertise and interests are multidisciplinary design optimization,
big data analytics, complex engineered systems, wind energy, power & energy systems, and renewable integration. This research has resulted in over 80 peer-reviewed journal and conference publications. He has received the best paper awards from Renewable Energy journal and IEEE Power & Energy Society General
Meeting. He is a senior member of IEEE and AIAA. He is a member of AIAA Multidisciplinary Design Optimization technical committee and ASME Solar Energy
Division technical committee.

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