Strictly convex loss functions for port-Hamiltonian based optimization algorithm for MTDC networks

Authors

Ernest Benedito, Dunstano del Puerto-Flores, Arnau Doria-Cerezo, Olivier van der Feltz, Jacquelien M.A. Scherpen

Abstract

In this work we propose a primal-dual method that can be cast in a port-Hamiltonian framework for minimizing the power losses in a multi-terminal DC network. The main contribution consists of proposing an alternative power loss function by means of a change of variables that translates the convex objective function into a strictly convex objective function. The results hold under some restrictive assumptions, but necessary to make steps towards a complete algorithm in future research. The obtained results are validated via numerical simulations.

Citation

• Journal: 2016 IEEE 55th Conference on Decision and Control (CDC)
• Year: 2016
• Volume:
• Issue:
• Pages: 7483–7488
• Publisher: IEEE
• DOI: 10.1109/cdc.2016.7799425

BibTeX

@inproceedings{Benedito_2016,
  title={{Strictly convex loss functions for port-Hamiltonian based optimization algorithm for MTDC networks}},
  DOI={10.1109/cdc.2016.7799425},
  booktitle={{2016 IEEE 55th Conference on Decision and Control (CDC)}},
  publisher={IEEE},
  author={Benedito, Ernest and del Puerto-Flores, Dunstano and Doria-Cerezo, Arnau and van der Feltz, Olivier and Scherpen, Jacquelien M.A.},
  year={2016},
  pages={7483--7488}
}

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