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EMS-Data-Based Load Modeling to Evaluate the Effect of Conservation Voltage Reduction at a National Level

Author

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  • Soon-Ryul Nam

    (Department of Electrical Engineering, Myongji University, Yongin 449-728, Korea)

  • Sang-Hee Kang

    (Department of Electrical Engineering, Myongji University, Yongin 449-728, Korea)

  • Joo-Ho Lee

    (Department of System Operation and Control, Korea Power Exchange, Seoul 135-791, Korea)

  • Eun-Jae Choi

    (Department of System Operation and Control, Korea Power Exchange, Seoul 135-791, Korea)

  • Seon-Ju Ahn

    (Department of Electrical Engineering, Chonnam National University, Gwangju 500-757, Korea)

  • Joon-Ho Choi

    (Department of Electrical Engineering, Chonnam National University, Gwangju 500-757, Korea)

Abstract

This paper proposes a linearized load model to evaluate the effect of conservation voltage reduction at a national level. In this model, the respective active and reactive linearizing parameters for active and reactive loads in a power system are estimated using energy management system (EMS) data resulting from conservation voltage reductions. To verify the validity of the linearized load model, PSS/E simulations were conducted for a test power system. Given that conservation voltage reductions are usually executed in the range of 2.0%–5.0%, the proposed model was found to be sufficient to accurately evaluate the effect of conservation voltage reduction. Additionally, Korean EMS data were used to estimate the linearizing parameters for aggregated loads in an actual power system.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:6:y:2013:i:8:p:3692-3705:d:27498
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    References listed on IDEAS

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    1. Dong, C. & Huang, G.H. & Cai, Y.P. & Xu, Y., 2011. "An interval-parameter minimax regret programming approach for power management systems planning under uncertainty," Applied Energy, Elsevier, vol. 88(8), pages 2835-2845, August.
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    3. Yong Zeng & Yanpeng Cai & Guohe Huang & Jing Dai, 2011. "A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty," Energies, MDPI, vol. 4(10), pages 1-33, October.
    4. Hsueh-Hsien Chang, 2012. "Non-Intrusive Demand Monitoring and Load Identification for Energy Management Systems Based on Transient Feature Analyses," Energies, MDPI, vol. 5(11), pages 1-21, November.
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    Cited by:

    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. Luciano C. Siebert & Adriana Sbicca & Alexandre Rasi Aoki & Germano Lambert-Torres, 2017. "A Behavioral Economics Approach to Residential Electricity Consumption," Energies, MDPI, vol. 10(6), pages 1-18, June.
    3. 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.

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