IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i8p1180-d107791.html
   My bibliography  Save this article

Optimal Voltage Control Using an Equivalent Model of a Low-Voltage Network Accommodating Inverter-Interfaced Distributed Generators

Author

Listed:
  • Mu-Gu Jeong

    (Department of Electrical and Computer Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea)

  • Young-Jin Kim

    (Department of Electrical Engineering, Pohang University of Science and Technology, 77 Cheongam-ro, Nam-gu, Pohang 37673, Korea)

  • Seung-Il Moon

    (Department of Electrical and Computer Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea)

  • Pyeong-Ik Hwang

    (Department of Electrical Engineering, Chosun University, 309 Pilmun-daero, Dong-gu, Gwangju 61452, Korea)

Abstract

The penetration of inverter-based distributed generators (DGs), which can control their reactive power outputs, has increased for low-voltage (LV) systems. The power outputs of DGs affect the voltage and power flow of both LV and medium-voltage (MV) systems that are connected to the LV system. Therefore, the effects of DGs should be considered in the volt/var optimization (VVO) problem of LV and MV systems. However, it is inefficient to utilize a detailed LV system model in the VVO problem because the size of the VVO problem is increased owing to the detailed LV system models. Therefore, in order to formulate and solve the VVO problem in an efficient way, in this paper, a new equivalent model for an LV system including inverter-based DGs is proposed. The proposed model is developed based on an analytical approach rather than a heuristic-fitting one, and it therefore enables the VVO problem to be solved using a deterministic algorithm (e.g., interior point method). In addition, a method to utilize the proposed model for the VVO problem is presented. In the case study, the results verify that the computational burden to solve the VVO problem is significantly reduced without loss of accuracy by the proposed model.

Suggested Citation

  • Mu-Gu Jeong & Young-Jin Kim & Seung-Il Moon & Pyeong-Ik Hwang, 2017. "Optimal Voltage Control Using an Equivalent Model of a Low-Voltage Network Accommodating Inverter-Interfaced Distributed Generators," Energies, MDPI, vol. 10(8), pages 1-19, August.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:8:p:1180-:d:107791
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/8/1180/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/10/8/1180/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hemmati, Reza & Hooshmand, Rahmat-Allah & Khodabakhshian, Amin, 2013. "State-of-the-art of transmission expansion planning: Comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 312-319.
    2. Pyeong-Ik Hwang & Seung-Il Moon & Seon-Ju Ahn, 2016. "A Conservation Voltage Reduction Scheme for a Distribution Systems with Intermittent Distributed Generators," Energies, MDPI, vol. 9(9), pages 1-18, August.
    3. Anna Rita Di Fazio & Mario Russo & Sara Valeri & Michele De Santis, 2016. "Sensitivity-Based Model of Low Voltage Distribution Systems with Distributed Energy Resources," Energies, MDPI, vol. 9(10), pages 1-16, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Faezeh Akhavizadegan & Lizhi Wang & James McCalley, 2020. "Scenario Selection for Iterative Stochastic Transmission Expansion Planning," Energies, MDPI, vol. 13(5), pages 1-18, March.
    2. Khalid A. Alnowibet & Ahmad M. Alshamrani & Adel F. Alrasheedi, 2023. "A Bilevel Stochastic Optimization Framework for Market-Oriented Transmission Expansion Planning Considering Market Power," Energies, MDPI, vol. 16(7), pages 1-15, April.
    3. Hamed Moazami Goodarzi & Mohammad Hosein Kazemi, 2017. "A Novel Optimal Control Method for Islanded Microgrids Based on Droop Control Using the ICA-GA Algorithm," Energies, MDPI, vol. 10(4), pages 1-17, April.
    4. Arcia-Garibaldi, Guadalupe & Cruz-Romero, Pedro & Gómez-Expósito, Antonio, 2018. "Future power transmission: Visions, technologies and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 285-301.
    5. Mete Şeref Ahunbay & Martin Bichler & Johannes Knörr, 2023. "Challenges in Designing Electricity Spot Markets," NBER Chapters, in: New Directions in Market Design, National Bureau of Economic Research, Inc.
    6. Yunhwan Lee & Hwachang Song, 2019. "A Reactive Power Compensation Strategy for Voltage Stability Challenges in the Korean Power System with Dynamic Loads," Sustainability, MDPI, vol. 11(2), pages 1-19, January.
    7. Zhang, Ning & Hu, Zhaoguang & Shen, Bo & Dang, Shuping & Zhang, Jian & Zhou, Yuhui, 2016. "A source–grid–load coordinated power planning model considering the integration of wind power generation," Applied Energy, Elsevier, vol. 168(C), pages 13-24.
    8. Sunoh Kim & Jin Hur, 2020. "Probabilistic Approaches to the Security Analysis of Smart Grid with High Wind Penetration: The Case of Jeju Island’s Power Grids," Energies, MDPI, vol. 13(21), pages 1-13, November.
    9. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S., 2018. "State-of-the-art generation expansion planning: A review," Applied Energy, Elsevier, vol. 230(C), pages 563-589.
    10. Zhe Zhang & Hang Yang & Xianggen Yin & Jiexiang Han & Yong Wang & Guoyan Chen, 2018. "A Load-Shedding Model Based on Sensitivity Analysis in on-Line Power System Operation Risk Assessment," Energies, MDPI, vol. 11(4), pages 1-17, March.
    11. Li, Can & Conejo, Antonio J. & Liu, Peng & Omell, Benjamin P. & Siirola, John D. & Grossmann, Ignacio E., 2022. "Mixed-integer linear programming models and algorithms for generation and transmission expansion planning of power systems," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1071-1082.
    12. Haas, J. & Cebulla, F. & Cao, K. & Nowak, W. & Palma-Behnke, R. & Rahmann, C. & Mancarella, P., 2017. "Challenges and trends of energy storage expansion planning for flexibility provision in low-carbon power systems – a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 603-619.
    13. Chong Cao & Zhouquan Wu & Bo Chen, 2020. "Electric Vehicle–Grid Integration with Voltage Regulation in Radial Distribution Networks," Energies, MDPI, vol. 13(7), pages 1-18, April.
    14. Jordehi, A. Rezaee, 2015. "Particle swarm optimisation (PSO) for allocation of FACTS devices in electric transmission systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1260-1267.
    15. Hongmei Li & Hantao Cui & Chunjie Li, 2019. "Distribution Network Power Loss Analysis Considering Uncertainties in Distributed Generations," Sustainability, MDPI, vol. 11(5), pages 1-17, March.
    16. Bichler, Martin & Knörr, Johannes, 2023. "Getting prices right on electricity spot markets: On the economic impact of advanced power flow models," Energy Economics, Elsevier, vol. 126(C).
    17. Wei Qi & Yong Liang & Zuo-Jun Max Shen, 2015. "Joint Planning of Energy Storage and Transmission for Wind Energy Generation," Operations Research, INFORMS, vol. 63(6), pages 1280-1293, December.
    18. Aman, M.M. & Jasmon, G.B. & Bakar, A.H.A. & Mokhlis, H. & Karimi, M., 2014. "Optimum shunt capacitor placement in distribution system—A review and comparative study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 429-439.
    19. Wook-Won Kim & Jong-Keun Park & Yong-Tae Yoon & Mun-Kyeom Kim, 2018. "Transmission Expansion Planning under Uncertainty for Investment Options with Various Lead-Times," Energies, MDPI, vol. 11(9), pages 1-19, September.
    20. Giuseppe Fusco & Mario Russo & Michele De Santis, 2021. "Decentralized Voltage Control in Active Distribution Systems: Features and Open Issues," Energies, MDPI, vol. 14(9), pages 1-31, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:10:y:2017:i:8:p:1180-:d:107791. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.