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Course paper / final thesis

Choice of optimizer for the yield optimized operation of a CSP plant under consideration of water saving

Starting date

2 March 2020

Duration of contract

6 months

Remuneration

up to German TVöD 5

Type of employment

Part-time

"Cutting-edge research requires excellent minds – particularly more females – at all levels. Launch your mission with us and send in your application now!" Prof. Pascale Ehrenfreund - Chair of the DLR Executive Board

Direct solar irradiation is essential for the use of Concentrated Solar Power (CSP) plants. Hence CSP plants are built in places with high direct solar irradiation. In general these are arid regions. This is a challenge since CSP plants also rely on the availability of water.

Water is used for various tasks in a CSP plant. The three main water consumers are wet-cooling, mirror cleaning and steam cycle blow down.

In the EU project "SOLWARIS", technologies and methods are being developed to reduce the water consumption of CSP plants. DLR is developing an O&M optimizer to help the power plant operator to run his CSP plant as efficiently as possible. The selection of a suitable optimization approach is subject of this master thesis.

The result of the optimizer should be a schedule according to which the operator can run the power plant as profitably as possible for the next three days. For example, you can influence the time of mirror cleaning and storage charging, but also valve positions in the piping for cooling and water recovery. The definition of the optimization task and the appropriate parameterization shall not be topic of the student work. Parameter sets proposed by the optimizer are passed on to a “black box”, which calculates the electricity generation, the water consummation and the financial yield. Based on these results, the optimizer searches for the optimal operation schedule. A gradient-based method is probably unsuitable in favor of the flexibility of the "black box".

The implementation of the optimizer is planned in Matlab or Phyton.

Steps:

  • Familiarization and understanding of optimization task
  • Support and definition of interfaces for planning the black box-optimizer system.
  • Research of possible optimization approaches
  • Well-founded selection of suitable optimization approaches
  • Implementation and testing of selected optimization approaches with the black box.
  • Evaluation and comparison of optimizer results and well-founded recommendation of the most convenient one

Your qualifications:

  • Field of study: computer science, Math, etc.
  • good analytical skills
  • very good knowledge in the field of optimization
  • Basic knowledge of Matlab, Python or other programming languages
  • Good oral and written skills in German and English language

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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Technical contact

Lisa Kaborn
Institute of Solar Research

Phone: +49 2203 601-2438

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Vacancy 46255

HR department Cologne

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DLR site Cologne, Headquarters

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DLR Institute of Solar Research

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