Can Berk Saner

PhD - Research Fellow


National University of Singapore



A Machine Learning-Based Privacy-Preserving Approach to Incorporate Distributed Generators in AC Optimal Power Flow


Conference paper


Burak Dindar, Can Berk Saner, Dogukan Yigit Polat, Huseyin Kemal Cakmak, Veit Hagenmayer
2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), IEEE, 2024

Cite

Cite

APA   Click to copy
Dindar, B., Saner, C. B., Polat, D. Y., Cakmak, H. K., & Hagenmayer, V. (2024). A Machine Learning-Based Privacy-Preserving Approach to Incorporate Distributed Generators in AC Optimal Power Flow. IEEE.


Chicago/Turabian   Click to copy
Dindar, Burak, Can Berk Saner, Dogukan Yigit Polat, Huseyin Kemal Cakmak, and Veit Hagenmayer. “A Machine Learning-Based Privacy-Preserving Approach to Incorporate Distributed Generators in AC Optimal Power Flow.” 2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE). IEEE, 2024.


MLA   Click to copy
Dindar, Burak, et al. A Machine Learning-Based Privacy-Preserving Approach to Incorporate Distributed Generators in AC Optimal Power Flow. IEEE, 2024.


BibTeX   Click to copy

@inproceedings{burak2024a,
  title = {A Machine Learning-Based Privacy-Preserving Approach to Incorporate Distributed Generators in AC Optimal Power Flow},
  year = {2024},
  publisher = {IEEE},
  series = {2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE)},
  author = {Dindar, Burak and Saner, Can Berk and Polat, Dogukan Yigit and Cakmak, Huseyin Kemal and Hagenmayer, Veit}
}



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