Solar Thermal Power Plants

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Solar Thermal Power Plants


Stuttgart


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Your mission:

You want to help building a renewable energy future? DLR Institute of Solar Research is one of the world’s leading research institutes working on all aspects of solar thermal power plants. Equipped with cost efficient thermal storage, the solar thermal electricity and heat production technology is one of the pillars of tomorrows sustainable energy supply. With over 50 plants and a total capacity of more than 2.5 GW already installed world-wide, more and more plant operation topics get into the focus of R&D activities. DLR supplements its activities in specialized measurements and plant simulation by automatic online monitoring of large solar installations. The PhD position is intended to develop ground-breaking technologies with cutting edge data analysis, deep learning, and statistical methods.

Parabolic trough solar fields as one solar thermal technology are large installations (up to several km2) consisting of individual collectors (up to 1000). Four to six of them are arranged as one loop. Each collector is equipped with its own drive and sensors, is individually cleaned and undergoes individual degradation. The output of the solar plant is at its optimum when all units operate according to their specification and are ideally clean. Measurement techniques for monitoring all parts of the field in detail are very costly and are only suitable for special measurement campaigns but not for regular plant operation. In power plant industry, methodologies based on statistics and machine learning are used to derive information on individual components or effects from the large number of operational data acquired in the plant. The energetic output of the solar field is the result of a number of different effects in the various components of the system (optical losses, incident angle effects, thermal losses of collectors, thermal losses of piping, inaccuracy of drives and structures, hydraulic effects, …). This, in combination with the lack of sufficient sensors in the field, makes it rather impossible to identify any degradation effects by direct measurements. Statistical methods allow tracking data over long time periods and thus identify systematic trends. Together with machine learning approaches these trends can be assigned to individual effects. Knowledge of current performance status of all components helps to develop cost-efficient maintenance strategies, opens the way of model predictive solar field control, and provides reliability data required for the financing of plants.

The objective of the PhD thesis is to develop fundamental concepts for condition monitoring of parabolic trough plants. Suitable methods should be identified and a monitoring concept developed and implemented. The benefits of the methodology will be worked out in simulation studies, tested in DLR’s own installations, and preferably in a real-size plant of an industrial partner. You are closely integrated in a team of highly motivated experts involved in various leading edge research projects. DLR Institute of Solar Research is working together with major industrial players and research teams world-wide offering the chance to get first-hand information on the state of the art technologies. The PhD project will be supervised by our head of the institute Prof. Robert Pitz-Paal in its role as professor at RWTH Aachen University. It is DLR’s mission to educate high-professionals for future career in research and industry. For this purpose, DLR offers a specialized graduate program for its PhD students with various advanced trainings.  

Your qualifications:

  • We are looking for a highly motivated PhD student eager to open the new research field of condition monitoring with us. You are our candidate if you:
  • have completed a master degree in engineering or similar
  • are used to take responsibility for your own work
  • show strong analytical skills
  • are creative thinking and have joy in new challenges
  • like to become part of an international scientific community
  • are familiar with programming languages e.g. C++ or Matlab
  • Of course, it is beneficial if you:
  • are experienced in solar engineering, preferably with solar thermal power plants
  • have experience in modeling and simulating of technical systems
  • have knowledge in statistical and machine learning methods
  • We expect that you can communicate well in English. You should have at least basic German knowledge and a clear commitment to improve your language skills.

Your benefits:

Look forward to a fulfilling job with an employer who appreciates your commitment and supports your personal and professional development. Our unique infrastructure offers you a working environment in which you have unparalled scope to develop your creative ideas and accomplish your professional objectives. Our human resources policy places great value on a healthy family and work-life-balance as well as equal opportunities for persons of all genders (m/f/non-binary). Individuals with disabilities will be given preferential consideration in the event their qualifications are equivalent to those of other candidates.

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Ansprechpartner

  • Dr. Tobias Hirsch

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Ansprechpartner

  • Dr. Tobias Hirsch

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