At the research group Wind Energy Systems, ForWind - Center for Wind Energy Research, Institute of Physics of the Carl von Ossietzky University of Oldenburg, there is a vacant PhD position starting as soon as possible for a
Research Assistant (f/m/d)
(Salary according to TV-L E13, 75%)
The research focus will be on
Minute-scale lidar-based power forecast of offshore wind farms
With scanning laser beams we are looking tenth of kilometres into the wind. Our vision is to reliably forecast power fluctuations of offshore wind farms for the upcoming half an hour. We want to realize this by a joint research project with several academic and industrial partners.
With the rising share of renewable energies in today's energy system, the demand for minute-scale power forecasts is continuously increasing. Such forecasts hold significant value to ensure grid stability, to reduce curtailment cost and to timely trade power. Especially the accurate prediction of so-called wind ramps, i.e. strong and sudden changes in wind speed or wind direction, is in this context important. In recent years, remote sensing-based forecasts with wind-lidar or -radar have gained increasing attention. Here, the incoming wind field is measured several kilometres upstream of the wind farm. Advection techniques are then applied to propagate wind vectors in time and space to the target turbines and allow to retrieve wind speed and power forecasts.
To make lidar-based forecasts more feasible for industry application, they need to be further developed, especially concerning the forecast horizon, the measurement set-up, scanning trajectories and the prediction of wind farm effects. Furthermore, the enhanced methodologies and new lidar devices have to be tested within the framework of an offshore measurement campaign.
The main goal of the PhD project is the development and validation of the remote sensing-based minute-scale power forecast of offshore wind farms.
Among others, the job will comprise:
- processing large amounts of data by combining lidar measurements, meteorological information and operational wind farm data
- uncertainty analysis of input data and forecasts
- optimisation of measurement set-up and lidar trajectories for forecasting applications by analysing atmospheric experimental and simulation data
- development of remote sensing-based minute-scale forecasting methodologies with emphasis on wind farm effects and the probabilistic forecasting of wind ramps
- implementation and validation of developed algorithms for real-time applications
The research will be conducted in close cooperation with several academic and industrial partners incl. a federal research institute, two manufacturers of lidar hardware, a power forecast provider, two wind farm and grid operators as well as a power trader.
Furthermore, the candidate will be given opportunities to actively improve personal, scientific and teaching skills.
Prerequisite is a qualifying university degree (diploma or master) in Meteorology, Physical Sciences, Mathematics, Engineering, Wind Energy, Remote Sensing or a similar field. The successful candidate is required to have:
- profound knowledge of at least two of the following three fields: experimental/numerical fluid dynamics, statistical analysis of large data amounts, measurement techniques
- extensive experience in programming with at least Matlab or Python
- high motivation and ability to work on a complex research topic
- fluency in communicating and reporting in English
The employment is initially limited until June 30th, 2023 with an intention for further prolongation up to a total of four years to facilitate a PhD.
The University of Oldenburg is dedicated to increase the percentage of female employees in the field of science. Therefore, female candidates are strongly encouraged to apply. In accordance to § 21 Section 3 NHG, female candidates with equal qualifications will be preferentially considered. Applicants with disabilities will be given preference in case of equal qualification.
Research environment at ForWind - University of Oldenburg
Wind energy research at the Carl von Ossietzky University of Oldenburg has gained international recognition by its integration into ForWind - Center for Wind Energy Research of the Universities of Oldenburg, Hannover and Bremen and into the national Wind Energy Research Alliance of the German Aerospace Center (DLR), Fraunhofer Institute for Wind Energy Systems (IWES) and ForWind. At Oldenburg, researchers from the fields of physics, meteorology and engineering are collaborating at the »Research Laboratory for Turbulence and Wind Energy Systems« centred on wind physics. Laboratory experiments, free-field measurements and HPC-based numerical simulations are utilized. Main topics include the description and modelling of wind turbulence, the analysis of interactions of turbulent atmospheric wind flow and wind energy systems as well as control of wind turbines and wind farms. State-of-the-art facilities comprise three turbulent wind tunnels, different sensing equipment for free-field measurements at on- and offshore wind farms and an own high-performance computing cluster. Two multi-lidar systems each equipped with three scanning lidars are of particular importance for the present project.
Preferably electronic applications should be referenced #UN58 and must be submitted preferred as one PDF file containing all materials in English or German to be given consideration no later than July 12th, 2020 to
Carl von Ossietzky University of Oldenburg
Institute of Physics, ForWind - Center for Wind Energy Research
Research Group Wind Energy Systems, Prof. Dr. Martin Kühn
Küpkersweg 70, 26129 Oldenburg, Germany
Phone +49 441 798 5061, Email wesys
The pdf file must include:
- A letter motivating the application (cover letter)
- Curriculum vitae
- Grade transcripts and BSc/MSc certificates
- Research statement, up to one page. The applicants are requested to write a research statement of their interest that is by preference related to the advertised PhD position.
A second PDF file containing the final thesis of the studies or relevant research papers (if available) is an optional attachment.