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State estimation in low-voltage grids by using artificial neural networks in consideration of optimal micro phasor measurement unit placement
M. Kelker, K. Schulte, J. Haubrock, in: NEIS 2020; Conference on Sustainable Energy Supply and Energy Storage Systems, 2020.
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Konferenzbeitrag
| Englisch
Autor*in
Erscheinungsjahr
Titel des Konferenzbandes
NEIS 2020; Conference on Sustainable Energy Supply and Energy Storage Systems
Konferenz
NEIS 2020; Conference on Sustainable Energy Supply and Energy Storage Systems
Konferenzort
Hamburg
Konferenzdatum
2020-05-14 – 2020-05-15
FH-PUB-ID
Zitieren
Kelker, Michael ; Schulte, Katrin ; Haubrock, Jens: State estimation in low-voltage grids by using artificial neural networks in consideration of optimal micro phasor measurement unit placement. In: NEIS 2020; Conference on Sustainable Energy Supply and Energy Storage Systems, 2020
Kelker M, Schulte K, Haubrock J. State estimation in low-voltage grids by using artificial neural networks in consideration of optimal micro phasor measurement unit placement. In: NEIS 2020; Conference on Sustainable Energy Supply and Energy Storage Systems. ; 2020.
Kelker, M., Schulte, K., & Haubrock, J. (2020). State estimation in low-voltage grids by using artificial neural networks in consideration of optimal micro phasor measurement unit placement. In NEIS 2020; Conference on Sustainable Energy Supply and Energy Storage Systems. Hamburg.
@inproceedings{Kelker_Schulte_Haubrock_2020, title={State estimation in low-voltage grids by using artificial neural networks in consideration of optimal micro phasor measurement unit placement}, booktitle={NEIS 2020; Conference on Sustainable Energy Supply and Energy Storage Systems}, author={Kelker, Michael and Schulte, Katrin and Haubrock, Jens}, year={2020} }
Kelker, Michael, Katrin Schulte, and Jens Haubrock. “State Estimation in Low-Voltage Grids by Using Artificial Neural Networks in Consideration of Optimal Micro Phasor Measurement Unit Placement.” In NEIS 2020; Conference on Sustainable Energy Supply and Energy Storage Systems, 2020.
M. Kelker, K. Schulte, and J. Haubrock, “State estimation in low-voltage grids by using artificial neural networks in consideration of optimal micro phasor measurement unit placement,” in NEIS 2020; Conference on Sustainable Energy Supply and Energy Storage Systems, Hamburg, 2020.
Kelker, Michael, et al. “State Estimation in Low-Voltage Grids by Using Artificial Neural Networks in Consideration of Optimal Micro Phasor Measurement Unit Placement.” NEIS 2020; Conference on Sustainable Energy Supply and Energy Storage Systems, 2020.
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