Optimized control design for power converters in power electronics embedded networks integrating grid model identification

Li, Kang; Dewar, David; Formentini, Andrea; Zanchetta, Pericle; Wheeler, Pat

Abstract

© 2018 IEEE The proliferation of power electronics systems and distributed generation in modern power networks has raised important issues regarding the effects that interconnected converters systems can have on the performance and stability of the whole grid. Interactions between locally optimized converters, designed not taking into account the external influence of the system in which they are operating, may lead to performance degradation or even system instability and failure. This paper will deal with the problem of power converters control design taking into account system interactions with other power converters in the grid. A globally optimized control tuning approach along with a state space grid identification method is here presented. Simulation and experimental results clearly show that the dynamic behaviour of the proposed method outperforms standard tuning techniques. A prototype embedded network composed by two power converters is built and the experimental results validate the effectiveness of proposed optimized control method.

Citation

Li, K., Dewar, D., Formentini, A., Zanchetta, P., & Wheeler, P. (2018). Optimized control design for power converters in power electronics embedded networks integrating grid model identification. In 2018 IEEE Industry Applications Society Annual Meeting (IAS2018). https://doi.org/10.1109/IAS.2018.8544592

• Conference Name: 2018 IEEE Industry Applications Society Annual Meeting (IAS2018)
• Conference Location: Portland, OR
• Start Date: Sep 23, 2018
• End Date: Sep 27, 2018
• Acceptance Date: Jul 1, 2018
• Online Publication Date: Nov 29, 2018
• Publication Date: Sep 23, 2018
• Deposit Date: Feb 14, 2019
• Publisher: Institute of Electrical and Electronics Engineers
• Book Title: 2018 IEEE Industry Applications Society Annual Meeting (IAS2018)
• ISBN: 9781538645369
• DOI: https://doi.org/10.1109/IAS.2018.8544592
• Public URL: https://nottingham-repository.worktribe.com/output/1549859
• Publisher URL: https://ieeexplore.ieee.org/document/8544592