Optimal Capacitor Placement and Rating for Large-Scale Utility Power Distribution Systems Employing Load-Tap-Changing Transformer Control

Evan S. Jones, Nicholas Jewell, Yuan Liao, Dan M. Ionel

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


Significant opportunity for savings in energy and investment through improved performance of power distribution systems exists in the optimal placement and rating of capacitors, a conventionally cost-effective and popular reactive power compensating technology. A novel optimal capacitor planning (OCP) procedure is proposed for large-scale utility power distribution systems, which is exemplified on an existing utility circuit of approximately 4,000 buses. An initial sensitivity analysis is employed to intelligently reduce OCP computation time and maintain quality of optimal configurations. Three optimization objectives are considered, including the minimization of total system active power losses, standard deviation of node voltages, and investment in total capacitor power rating. Eight multi-objective optimization methods that employ the non-dominated sorting algorithm III (NSGA-III) concept are compared to determine individual merits. Differences between the methods include the incorporation of a penalty constraint for voltage violations and the automatic readjustment of load-tap-changing (LTC) transformer tap settings for proposed capacitor re-configurations concurrently within the optimizer, which ensures peak system performance and fair comparison to the reference case. A multi-step model conversion process was developed with OpenDSS to enable the OCP procedure to be generally applicable to real large-scale utility circuits. OCP is performed for three example sub-circuits served by a substation with a 48MW, 9Mvar peak load, which represents the most extreme case and offers the best opportunity for savings. Example configurations from the resulting Pareto sets through a pseudo-weight vector approach are also analyzed through a systematic procedure of comparison between the most extreme configuration types to inform configuration selection.

Original languageEnglish
Pages (from-to)19324-19338
Number of pages15
JournalIEEE Access
StatePublished - 2023

Bibliographical note

Funding Information:
This research was funded in part by the Department of Education's Graduate Assistance in Areas of National Need (GAANN) Fellowship Program through the University of Kentucky Electrical and Computer Engineering Department and the Louisville Gas and Electric and Kentucky Utilities (LG&E and KU), part of the PPL Corporation family of companies.

Publisher Copyright:
© 2013 IEEE.


  • Capacitor
  • control
  • differential evolution
  • load-tap-changing transformers
  • non-dominated sorting genetic algorithm III
  • openDSS
  • optimization
  • power distribution systems
  • sensitivity analysis

ASJC Scopus subject areas

  • Engineering (all)
  • Materials Science (all)
  • Computer Science (all)


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