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Grid-Connected, Data-Driven Inverter Control, Theory to Hardware

Sebastian Graf, Keith Moffat

2022Englishelectricityelectronicsdata-driven controlpredictive controlinverter controlpower systems

Abstract

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Grid-connected inverter control is challenging to implement due to the difficulty of obtaining and maintaining an accurate grid model. Direct Data-Driven Predictive Control provides a model-free alternative to traditional model-based control methods. This paper describes how the recently-proposed Transient Predictive Control (TPC) can be used for real-world, plug-and-play inverter control. The following hypotheses were tested: 1) The TPC algorithm can be run online using standard hardware, and 2) TPC, which is derived using Linear Time-Invariant assumptions, is effective for grid-connected inverter control, which is a nonlinear and time-varying system. Experiments conducted on a two-converter benchtop setup and at the CoSES Laboratory on a 25 kV A converter connected to the Munich grid support these hypotheses.

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Cite This Work

@article{0fbce7a5-044f-4160-bc4f-b75b4703e40d,
  title={Grid-Connected, Data-Driven Inverter Control, Theory to Hardware},
  author={Sebastian Graf and Keith Moffat},
  year={2022},
  language={English}
}
TY  - JOUR
TI  - Grid-Connected, Data-Driven Inverter Control, Theory to Hardware
AU  - Sebastian Graf
AU  - Keith Moffat
PY  - 2022
LA  - English
ER  -

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