Evaluation of conservation voltage reduction with analytic hierarchy process: A decision support framework in grid operations planning

Kyungsung An, Hao Jan Liu, Hao Zhu, Zhao Yang Dong, Kyeon Hur

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


This paper presents a systematic framework to evaluate the performance of conservation voltage reduction (CVR) by determining suitable substations for CVR in operations planning. Existing CVR planning practice generally only focuses on the energy saving aspect without taking other underlying attributes into account, i.e., network topology and reduced voltage effects on other substations. To secure the desired operating reserve and avoid any adverse impacts, these attributes should be considered for implementing CVR more effectively. This research develops a practical decision-making framework based on the analytic hierarchy process (AHP) to quantify several of the aforementioned attributes. Candidate substations for CVR deployment are prioritized such that performances are compared in terms of power transfer distribution factor (PTDF), voltage sensitivity factor (VSF), and CVR factor. In addition, to meet a specified reserve requirement, an integer programming approach is adopted to select potential substations for CVR implementations. Case studies for a Korean electric power system under diverse operating conditions are performed to demonstrate the effectiveness of the proposed method.

Original languageEnglish
Article number1074
Issue number12
Publication statusPublished - 2016 Dec

Bibliographical note

Funding Information:
Acknowledgments: This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education, Science and Technology (No. 2016R1D1A1B03930582). This work was supported by the Yonsei University Research Fund Joint International Project Development Fund (JIPDF) Supporting Program of 2016 (project No.: 2016-12-0046).

Publisher Copyright:
© 2016 by the authors.

All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment
  • Fuel Technology
  • Energy Engineering and Power Technology
  • Energy (miscellaneous)
  • Control and Optimization
  • Electrical and Electronic Engineering


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