Master Thesis in Power System Model Reduction

Vor 2 Tagen


Erlangen, Bayern, Deutschland Siemens Energy Vollzeit
Master Thesis Opportunity in Power System Model Reduction

About the Project

We are seeking a highly motivated and skilled Master student to work on a dynamic power system model reduction project in DIgSILENT PowerFactory. The successful candidate will have the opportunity to contribute to the development of innovative power system analysis and simulation tools.

Key Responsibilities

  • Develop and implement dynamic model reduction algorithms in Python
  • Design and test improvements to the model reduction techniques using power system analysis and algorithmic approaches
  • Evaluate and present project results

Requirements

  • Currently pursuing a Master's degree in electrical engineering, power engineering, or a related field
  • Good academic record and relevant knowledge of power systems and control systems
  • Experience with power system simulation tools, such as DIgSILENT PowerFactory
  • Good knowledge of power system dynamics and control theory
  • Familiarity with Python and algorithms

What We Offer

  • A dynamic and collaborative work environment
  • The opportunity to work on a cutting-edge project with a leading company in the energy sector
  • Support and guidance from experienced professionals

Location

Germany, Bayern, Erlangen

Mode of Employment

Part-time, Fixed Term



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