报告人简介:Prof.Pierre Pinson 
Dr. Pierre Pinson is a Professor at the Centre for Electric Power and Energy (CEE) of the Technical university of Denmark, also heading the Energy Analytics & Markets group. He holds a M.Sc. In Applied Mathematics (INSA Toulouse, France) and a Ph.D. In Energetics from Ecole de Mines de Paris (France, now known as Mines ParisTech). He is a Senior Member of the IEEE Power & Energy Society, also acting as an Editor for the IEEE Transactions on Power Systems, the International Journal of Forecasting, and Wind Energy. His main research interests are centered around the proposal and application of mathematical methods for electricity markets and power systems operations. Prof. Pinson has published extensively in some of the leading journals in Meteorology, Power Systems Engineering, Statistics and Operations Research. He is a regular contributing and invited speaker at numerous international conferences. He has been a visiting researcher at the University of Oxford (Mathematical Institute) and the University of Washington in Seattle (Dpt. of Statistics). Early May 2014, he was placed on the Recharge4040 list (40 under 40), a list of the world’s brightest young energy pioneers.
Prof. Pierre Pinson

报告内容
• Title: Offshore wind power generation: Characterizing, modeling and forecasting its fluctuations
• Wind generation capacities have been deployed widely onshore, though new large wind farms are to be increasingly located offshore. These offshore wind farms concentrate a large number of more powerful turbines, while they are subject to wind conditions different from those that onshore wind farms experience. Integrating the power generation from these wind farms into power systems and through electricity markets is a current challenge in Northern Europe –- it will most likely be the same in other areas of the world. The aim of this talk is to focus on the dynamics of the power generation itself, and on our attempts at modeling and forecasting such power fluctuations. For that, we will first characterize the regime-switching behavior of offshore wind power dynamics, also trying to understand what could induce these regime changes. A number of advanced forecasting approaches, which account for these effects in a computationally efficient manner, will be introduced . Finally, we will describe a world-first experiment, Radar@Sea, where weather radars (both onshore and offshore) were employed to better characterize, model and predict offshore wind power fluctuations. Perspectives stemming for the use of modern remote-sensing technology will be given.