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Master Thesis, Reinforcement learning at FACTS

Publicerad 2019-04-17


Om uppdragsgivaren
You will be part of the Business Unit Grid Integration, located in Västerås. FACTS Flexible Alternating Current Transmission Systems technologies provide more power and control in existing AC as well as green-field networks and have minimal environmental impact. With a complete portfolio and in-house manufacturing of key components, ABB is a reliable partner in shaping the grid of the future. Please find out more about our world leading technology at www.abb.com/facts.

Beskrivning av examensarbetet
At FACTS you will aid in creating a more sustainable future. The increase of available measurements, growth of real time processing capacity and communication abilities is changing the opportunities in the power system landscape. There is a potential to utilize more measurement data, Reinforcement Learning and a FACTS device for optimization purposes.
The task would include:
• Create suitable test networks
• Investigate and develop prototype algorithm based on latest advancements in deep Reinforcement Learning
• Train, tune and test the algorithms on the networks and demonstrate policy optimality

Requirements:
We are looking for you who are studying a university master program within a relevant technical area along with an interest within artificial intelligence or Reinforcement Learning. Experience in Reinforcement Learning or programming is positive. We aim to start the thesis in early September.

Kontaktperson
Jonathan Hanning
jonathan.hanning@se.abb.com
+4621 324 406


Tillbaka
  Utbildningsområde
Teknik/Energiteknik/Miljö/Transport

Uppdragsgivare
ABB AB

Ort
Västerås

Sista ansökningdag
2019-07-16

Genomförandeperiod
2019, HT

Länkar
Exjobb


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