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Evaluation of Conservation Voltage Reduction with Analytic Hierarchy Process: A Decision Support Framework in Grid Operations Planning

Author

Listed:
  • Kyungsung An

    (School of Electrical and Electronic Engineering, Yonsei University, Seoul 120-149, Korea)

  • Hao Jan Liu

    (Department of Electrical and Computer Engineering, The University of Illinois at Urbana-Champaign, 1308 West Main St, Urbana, IL 61801, USA)

  • Hao Zhu

    (Department of Electrical and Computer Engineering, The University of Illinois at Urbana-Champaign, 1308 West Main St, Urbana, IL 61801, USA)

  • Zhao Yang Dong

    (School of Electrical and Information Engineering, University of Sydney, Sydney, NSW 2006, Australia)

  • Kyeon Hur

    (School of Electrical and Electronic Engineering, Yonsei University, Seoul 120-149, Korea)

Abstract

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.

Suggested Citation

  • Kyungsung An & Hao Jan Liu & Hao Zhu & Zhao Yang Dong & Kyeon Hur, 2016. "Evaluation of Conservation Voltage Reduction with Analytic Hierarchy Process: A Decision Support Framework in Grid Operations Planning," Energies, MDPI, vol. 9(12), pages 1-15, December.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:12:p:1074-:d:85422
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    References listed on IDEAS

    as
    1. Soon-Ryul Nam & Sang-Hee Kang & Joo-Ho Lee & Seon-Ju Ahn & Joon-Ho Choi, 2013. "Evaluation of the Effects of Nationwide Conservation Voltage Reduction on Peak-Load Shaving Using SOMAS Data," Energies, MDPI, vol. 6(12), pages 1-13, December.
    2. Soon-Ryul Nam & Sang-Hee Kang & Joo-Ho Lee & Eun-Jae Choi & Seon-Ju Ahn & Joon-Ho Choi, 2013. "EMS-Data-Based Load Modeling to Evaluate the Effect of Conservation Voltage Reduction at a National Level," Energies, MDPI, vol. 6(8), pages 1-14, July.
    3. Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, July.
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    Cited by:

    1. Imke Lammers & Maarten J. Arentsen, 2017. "Rethinking Participation in Smart Energy System Planning," Energies, MDPI, vol. 10(11), pages 1-16, October.
    2. Anthony Igiligi & Armin Vielhauer & Mathias Ehrenwirth & Christian Hurm & Thorsten Summ & Christoph Trinkl & Daniel Navarro Gevers, 2023. "Assessment of Conservation Voltage Reduction in Distribution Networks with Voltage Regulating Distribution Transformers," Energies, MDPI, vol. 16(7), pages 1-14, March.
    3. Weixin Yang & Lingguang Li, 2017. "Efficiency Evaluation and Policy Analysis of Industrial Wastewater Control in China," Energies, MDPI, vol. 10(8), pages 1-18, August.

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