AI for Stability Optimization in Low Voltage Direct Current Microgrids
Roeder G, Schwanninger R, Wienzek P, Kerscher M, Wunder B, Schellenberger M (2024)
Publication Language: English
Publication Type: Book chapter / Article in edited volumes
Publication year: 2024
Publisher: Springer
Edited Volumes: Unlocking Artificial Intelligence. From Theory to Applications
City/Town: Cham
Pages Range: 269-285
ISBN: 978-3-031-64831-1
DOI: 10.1007/978-3-031-64832-8_14
Abstract
Low voltage direct current (LVDC) is an enabling technology to foster a sustainable resilient energy supply. LVDC microgrids comprising energy generators, storage systems, and loads work as independently controlled units in connection with common alternating current networks. Precise digitized control applying intelligent power converters enables new AI-based approaches for DC microgrid layout and operation. In this work, a new method involving connected machine learning and optimization is established together with a novel measurement system, which enables the measurement and improvement of microgrid stability. The application is successfully validated by experimental assessment on a testbed with a four-terminal DC network operating at a voltage of 380 VDC and the advantages of the AI-based approach are demonstrated.
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Germany (DE)How to cite
APA:
Roeder, G., Schwanninger, R., Wienzek, P., Kerscher, M., Wunder, B., & Schellenberger, M. (2024). AI for Stability Optimization in Low Voltage Direct Current Microgrids. In Christopher Mutschler, Christian Münzenmayer, Norman Uhlmann, Alexander Martin (Eds.), Unlocking Artificial Intelligence. From Theory to Applications. (pp. 269-285). Cham: Springer.
MLA:
Roeder, Georg, et al. "AI for Stability Optimization in Low Voltage Direct Current Microgrids." Unlocking Artificial Intelligence. From Theory to Applications. Ed. Christopher Mutschler, Christian Münzenmayer, Norman Uhlmann, Alexander Martin, Cham: Springer, 2024. 269-285.
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