Siemens Careers

Power Plant Operation Optimization: Economic dispatch of combined cyle power plants - Master Thesis Spring 2019

Finspang, Sweden

English (UK)

Job Description

Are you a master student planning to write your Master Thesis during spring 2019?

Join us on our journey into the future #FutureMakers#Siemens

Be part of an open and dynamic workplace where professional and personal development is high on the agenda. By making sustainable energy solutions more cost effective, developing new technologies for the future's smart industry and electrifying passenger and freight transport, we make reality of our vision of a sustainable world.

We are now looking for a student to take on the assignment” Power Plant Operation Optimization: Economic dispatch of combined cycle power plants”.

The assignment

This Master thesis is part of Siemens efforts done to develop decision support algorithms to help the power plant operators in their daily life with the decisions they need to take. The final goal of the project is to develop a mathematical model that minimizes the fuel cost of the studied combined cycle power plants under different constraints as for instance: power demand, maximum available capacity, start-up time etc. Previous work has been done within the data analytics department in this field, but only considering the gas turbines of the combined cycle. Now, the challenge is to incorporate the steam turbines to the optimization and to model the short-term cost of the entire power plant.

Students will be provided with access to all the needed sensor data to develop the efficiency models of the whole power plants and to incorporate the constraints of the optimization. They will be working closely with domain experts with strong backgrounds in: thermodynamics, reliability analysis, data mining, machine learning and mathematical optimization.

As a first approach the student will built the model to optimize the operation with true data. Then, if the first stage of the project is completed, the student will study the pre-schedule of the machines two days before (unit-commitment) depending on the forecasted demand and the future available capacity. Predictive models for these parameters will be provided.

Additionally, the student will study the possibility of including additional constraints to the model as the equivalent operating cycles (EOC) or the equivalent operating hours (EOH) to optimize the maintenance costs as well.

Who are you?

  • The project is suitable for one student with academic background in data science,   energy systems, industrial engineering, computer science, mathematics or another relevant field.
  • As a student you have strong analytical skills and solid mathematical background.
  • You are interested in data analytics (especially in prescriptive analytics) and hold good programming skills (preferable: Python, R or Julia)


Do not hesitate - apply today via ref nr 82816 and no later than 15 November. For questions about the role please contact recruiting manager Erik Ärlebäck on +46 (0)122 81291.

Type of contract:
Fixed term – approximately 6 months.
Compensation type: hourly paid.

Trade Union representatives:
Christine Lindström, Unionen, 0122-817 28
Simon Bruneflod, Sveriges Ingenjörer, 0122-842 24
Jan Lundgren, Ledarna, 0122-812 33
Kenth Gustavsson, IF Metall, 0122-815 25


In this recruitment we renounce all calls relating to advertising and recruitment support.

Job ID: 82816

Organisation: Power Generation Services

Experience Level: Student (Not Yet Graduated)

Job Type: Full-time

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