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Peak-Load Management of Distribution Network Using Conservation Voltage Reduction and Dynamic Thermal Rating

Author

Listed:
  • Ramin Nourollahi

    (Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz P.O. Box 5166616471, Iran)

  • Pouya Salyani

    (Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz P.O. Box 5166616471, Iran)

  • Kazem Zare

    (Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz P.O. Box 5166616471, Iran)

  • Behnam Mohammadi-Ivatloo

    (Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz P.O. Box 5166616471, Iran)

  • Zulkurnain Abdul-Malek

    (School of Electrical Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia)

Abstract

The peak-load management of a distribution network (DN) has gained attention by increasing the electric power consumption on the demand side. By developing smart-grid infrastructures, effective utilization of the DN’s components and proper management of the DN would create a valuable solution for DN operators. Hence, in this paper, a peak-load management framework is proposed in which the real-time rating of the components and voltage-dependent features of the electric loads help the DN operator handle the peak times successfully. In addition to the individual advantages of efficient operation of the DN, more practical results are obtained by combining the conservation voltage reduction (CVR) and dynamic thermal rating (DTR) of the DN’s lines and transformers. Based on the obtained results, compared to the individual implementation of CVR, the cost-saving level is increased significantly during the peak events using the simultaneous utilization of DTR and CVR. Furthermore, a discussion is presented about the current problems of the feeders supplying the voltage-dependent constant-power loads during CVR utilization, which is resolved by the dynamic rating of the DN’s components.

Suggested Citation

  • Ramin Nourollahi & Pouya Salyani & Kazem Zare & Behnam Mohammadi-Ivatloo & Zulkurnain Abdul-Malek, 2022. "Peak-Load Management of Distribution Network Using Conservation Voltage Reduction and Dynamic Thermal Rating," Sustainability, MDPI, vol. 14(18), pages 1-17, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:18:p:11569-:d:915990
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    References listed on IDEAS

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    1. Hossain, Md Alamgir & Pota, Hemanshu Roy & Squartini, Stefano & Abdou, Ahmed Fathi, 2019. "Modified PSO algorithm for real-time energy management in grid-connected microgrids," Renewable Energy, Elsevier, vol. 136(C), pages 746-757.
    2. Yu, Dongmin & liu, Huanan & Bresser, Charis, 2018. "Peak load management based on hybrid power generation and demand response," Energy, Elsevier, vol. 163(C), pages 969-985.
    3. Dashti, Reza & Afsharnia, Saeed & Ghasemi, Hassan, 2010. "A new long term load management model for asset governance of electrical distribution systems," Applied Energy, Elsevier, vol. 87(12), pages 3661-3667, December.
    4. Aalami, H.A. & Moghaddam, M. Parsa & Yousefi, G.R., 2010. "Demand response modeling considering Interruptible/Curtailable loads and capacity market programs," Applied Energy, Elsevier, vol. 87(1), pages 243-250, January.
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    Cited by:

    1. Mithila Seva Bala Sundaram & ChiaKwang Tan & Jeyraj Selvaraj & Ab. Halim Abu Bakar, 2023. "Energy Savings for Various Residential Appliances and Distribution Networks in a Malaysian Scenario," Energies, MDPI, vol. 16(13), pages 1-18, June.
    2. Zhang, Hui & Wang, Jiye & Zhao, Xiongwen & Yang, Jingqi & Bu sinnah, Zainab Ali, 2023. "Modeling a hydrogen-based sustainable multi-carrier energy system using a multi-objective optimization considering embedded joint chance constraints," Energy, Elsevier, vol. 278(C).

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