Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Conferences, Workshops, Symposiums, and Seminars
  4. A Novel Method for the Optimal Parameter Selection of Discrete-Time Switch Model
 
conference paper

A Novel Method for the Optimal Parameter Selection of Discrete-Time Switch Model

Razzaghi, Reza  
•
Foti, Chrysanthi
•
Paolone, Mario  
Show more
Høidalen, Hans Kristian
•
Uglesic, Ivo
2013
Proceedings of the 10th International Conference on Power Systems Transients (IPST 2013)
10th International Conference on Power Systems Transients

The paper proposes a novel method for the optimal parameter selection of the discrete-time switch model used in circuit solvers that adopt the Fixed Admittance Matrix Nodal Method (FAMNM) approach. As known, FAMNM-based circuit solvers allow to reach efficient computation times since they do not need the inversion of the circuit nodal admittance matrix. However, these solvers need to optimally tune the so-called discrete switch conductance, since this parameter might largely affect the simulations accuracy. Within this context, the method proposed in the paper minimizes the distance between the eigenvalues of the original circuit’s nodal admittance matrix with those associated with the presence of the discrete-time switches. The method is proven to provide values of the discrete-time switch conductance that maximize the simulation accuracy and minimize the losses on this artificial parameter. The performances of the proposed method are finally validated by making reference to two test cases: (i) a circuit composed of RLC elements, (ii) a network model that includes a single-phase transmission line.

  • Files
  • Details
  • Metrics
Loading...
Thumbnail Image
Name

184.pdf

Access type

openaccess

Size

542.25 KB

Format

Adobe PDF

Checksum (MD5)

35030c8de3c707ce8ccb1c9a4f924ed9

Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés