Dynamic Distribution Factors

Abdullah Al-Digs, Sairaj V. Dhople, Yu Christine Chen

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This paper proposes an approach to obtain dynamic versions of static distribution factors, such as power-transfer, line-outage, and outage-transfer distribution factors. With the proposed dynamic distribution factors (DDFs), one can predict line flows over the post-contingency transient period with the same computational effort as obtaining static distribution factors. Our development centers on deriving closed-form expressions that approximate generator outputs through the post-contingency transient period with a reduced-order aggregate dynamical model to recover dynamic generator participation factors. The full suite of DDFs can then be derived by combining these dynamic generator participation factors with injection shift factors, i.e., static linear sensitivities of line active-power flows with respect to nodal active-power injections, computed at the pre-disturbance steady-state operating point. We illustrate the accuracy and computational benefits of the proposed DDFs via numerical case studies involving the New England test system.

Original languageEnglish (US)
Article number8718323
Pages (from-to)4974-4983
Number of pages10
JournalIEEE Transactions on Power Systems
Volume34
Issue number6
DOIs
StatePublished - Nov 2019

Bibliographical note

Funding Information:
This work was supported by the Natural Sciences and Engineering Research Council of Canada, funding reference RGPIN-2016-04271 and PGSD3- 519078-2018. The work of S. V. Dhople was supported by the National Science Foundation underGrant 1453921.

Funding Information:
Manuscript received December 2, 2018; revised April 3, 2019; accepted May 11, 2019. Date of publication May 20, 2019; date of current version October 24, 2019. This work was supported by the Natural Sciences and Engineering Research Council of Canada, funding reference RGPIN-2016-04271 and PGSD3-519078-2018. The work of S. V. Dhople was supported by the National Science Foundation under Grant 1453921. Paper no. TPWRS-01815-2018. (Corresponding author: Yu Christine Chen.) A. Al-Digs and Y. C. Chen are with the Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, BC V6T 1Z4, Canada (e-mail: aldigs@ece.ubc.ca; chen@ece.ubc.ca).

Keywords

  • Contingency analysis
  • distribution factors
  • injection shift factors
  • line-outage distribution factors
  • outage-transfer distribution factors
  • participation factors
  • power-transfer distribution factors
  • reduced-order models

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