IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v9y2016i9p666-d76499.html
   My bibliography  Save this article

A Conservation Voltage Reduction Scheme for a Distribution Systems with Intermittent Distributed Generators

Author

Listed:
  • Pyeong-Ik Hwang

    (Korea Electric Power Research Institute (KEPRI), 105 Munji-Ro, Yuseong-gu, Daejeon 34056, Korea)

  • Seung-Il Moon

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

  • Seon-Ju Ahn

    (Department of Electrical Engineering, Chonnam National University, 77 Yongbong-ro, Buk-gu, Gwangju 61186, Korea)

Abstract

In this paper, a conservation voltage reduction (CVR) scheme is proposed for a distribution system with intermittent distributed generators (DGs), such as photovoltaics and wind turbines. The CVR is a scheme designed to reduce energy consumption by lowering the voltages supplied to customers. Therefore, an unexpected under-voltage violation can occur due to the variation of active power output from the intermittent DGs. In order to prevent the under-voltage violation and improve the CVR effect, a new reactive power controller which complies with the IEEE Std. 1547 TM , and a parameter determination method for the controller are proposed. In addition, an optimal power flow (OPF) problem to determine references for the resources of CVR is formulated with consideration of the intermittent DGs. The proposed method is validated using a modified IEEE 123-node test feeder. With the proposed method, the voltages of the test system are maintained to be greater than the lower bound, even though the active power outputs of the DGs are varied. Moreover, the CVR effect is improved compared to that used with the conventional reactive power control methods.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jeners:v:9:y:2016:i:9:p:666-:d:76499
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/9/9/666/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/9/9/666/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Antonio Bracale & Pierluigi Caramia & Guido Carpinelli & Anna Rita Di Fazio & Gabriella Ferruzzi, 2013. "A Bayesian Method for Short-Term Probabilistic Forecasting of Photovoltaic Generation in Smart Grid Operation and Control," Energies, MDPI, vol. 6(2), pages 1-15, February.
    2. Soroudi, Alireza & Amraee, Turaj, 2013. "Decision making under uncertainty in energy systems: State of the art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 376-384.
    3. 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.
    4. Youcef Ettoumi, F. & Mefti, A. & Adane, A. & Bouroubi, M.Y., 2002. "Statistical analysis of solar measurements in Algeria using beta distributions," Renewable Energy, Elsevier, vol. 26(1), pages 47-67.
    5. Manbachi, Moein & Farhangi, Hassan & Palizban, Ali & Arzanpour, Siamak, 2016. "Smart grid adaptive energy conservation and optimization engine utilizing Particle Swarm Optimization and Fuzzification," Applied Energy, Elsevier, vol. 174(C), pages 69-79.
    6. Pyeong-Ik Hwang & Seung-Il Moon & Seon-Ju Ahn, 2013. "A Vector-Controlled Distributed Generator Model for a Power Flow Based on a Three-Phase Current Injection Method," Energies, MDPI, vol. 6(8), pages 1-19, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.

    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. Ahmad Abuelrub & Osama Saadeh & Hussein M. K. Al-Masri, 2018. "Scenario Aggregation-Based Grid-Connected Photovoltaic Plant Design," Sustainability, MDPI, vol. 10(4), pages 1-13, April.
    2. Marcin Rabe & Dalia Streimikiene & Yuriy Bilan, 2019. "The Concept of Risk and Possibilities of Application of Mathematical Methods in Supporting Decision Making for Sustainable Energy Development," Sustainability, MDPI, vol. 11(4), pages 1-24, February.
    3. Antonio Bracale & Pierluigi Caramia & Guido Carpinelli & Anna Rita Di Fazio & Gabriella Ferruzzi, 2013. "A Bayesian Method for Short-Term Probabilistic Forecasting of Photovoltaic Generation in Smart Grid Operation and Control," Energies, MDPI, vol. 6(2), pages 1-15, February.
    4. Guoqiang Sun & Wenxue Wang & Yi Wu & Wei Hu & Zijun Yang & Zhinong Wei & Haixiang Zang & Sheng Chen, 2019. "A Nonlinear Analytical Algorithm for Predicting the Probabilistic Mass Flow of a Radial District Heating Network," Energies, MDPI, vol. 12(7), pages 1-20, March.
    5. Ahmad, Muhammad Waseem & Mourshed, Monjur & Rezgui, Yacine, 2018. "Tree-based ensemble methods for predicting PV power generation and their comparison with support vector regression," Energy, Elsevier, vol. 164(C), pages 465-474.
    6. Weitzel, Timm & Glock, Christoph H., 2018. "Energy management for stationary electric energy storage systems: A systematic literature review," European Journal of Operational Research, Elsevier, vol. 264(2), pages 582-606.
    7. Ferruzzi, Gabriella & Cervone, Guido & Delle Monache, Luca & Graditi, Giorgio & Jacobone, Francesca, 2016. "Optimal bidding in a Day-Ahead energy market for Micro Grid under uncertainty in renewable energy production," Energy, Elsevier, vol. 106(C), pages 194-202.
    8. Qingwu Gong & Jiazhi Lei & Jun Ye, 2016. "Optimal Siting and Sizing of Distributed Generators in Distribution Systems Considering Cost of Operation Risk," Energies, MDPI, vol. 9(1), pages 1-18, January.
    9. Ghahramani, Mehrdad & Nazari-Heris, Morteza & Zare, Kazem & Mohammadi-Ivatloo, Behnam, 2019. "Energy and reserve management of a smart distribution system by incorporating responsive-loads /battery/wind turbines considering uncertain parameters," Energy, Elsevier, vol. 183(C), pages 205-219.
    10. Antonio Bracale & Pasquale De Falco, 2015. "An Advanced Bayesian Method for Short-Term Probabilistic Forecasting of the Generation of Wind Power," Energies, MDPI, vol. 8(9), pages 1-22, September.
    11. Hossein Shayeghi & Elnaz Shahryari & Mohammad Moradzadeh & Pierluigi Siano, 2019. "A Survey on Microgrid Energy Management Considering Flexible Energy Sources," Energies, MDPI, vol. 12(11), pages 1-26, June.
    12. Yao, Xing & Yi, Bowen & Yu, Yang & Fan, Ying & Zhu, Lei, 2020. "Economic analysis of grid integration of variable solar and wind power with conventional power system," Applied Energy, Elsevier, vol. 264(C).
    13. Kalim Ullah & Sajjad Ali & Taimoor Ahmad Khan & Imran Khan & Sadaqat Jan & Ibrar Ali Shah & Ghulam Hafeez, 2020. "An Optimal Energy Optimization Strategy for Smart Grid Integrated with Renewable Energy Sources and Demand Response Programs," Energies, MDPI, vol. 13(21), pages 1-17, November.
    14. Anh Ngoc-Lan Huynh & Ravinesh C. Deo & Duc-Anh An-Vo & Mumtaz Ali & Nawin Raj & Shahab Abdulla, 2020. "Near Real-Time Global Solar Radiation Forecasting at Multiple Time-Step Horizons Using the Long Short-Term Memory Network," Energies, MDPI, vol. 13(14), pages 1-30, July.
    15. Wolfram Rozas & Rafael Pastor-Vargas & Angel Miguel García-Vico & José Carpio, 2023. "Consumption–Production Profile Categorization in Energy Communities," Energies, MDPI, vol. 16(19), pages 1-27, October.
    16. Alexandros Korkovelos & Dimitrios Mentis & Morgan Bazilian & Mark Howells & Anwar Saraj & Sulaiman Fayez Hotaki & Fanny Missfeldt-Ringius, 2020. "Supporting Electrification Policy in Fragile States: A Conflict-Adjusted Geospatial Least Cost Approach for Afghanistan," Sustainability, MDPI, vol. 12(3), pages 1-34, January.
    17. Rosato, Antonello & Panella, Massimo & Andreotti, Amedeo & Mohammed, Osama A. & Araneo, Rodolfo, 2021. "Two-stage dynamic management in energy communities using a decision system based on elastic net regularization," Applied Energy, Elsevier, vol. 291(C).
    18. Barbie, Eli & Rabinovici, Raul & Kuperman, Alon, 2020. "Analytic formulation and optimization of weighted total harmonic distortion in single-phase staircase modulated multilevel inverters," Energy, Elsevier, vol. 199(C).
    19. Alessandrini, S. & Delle Monache, L. & Sperati, S. & Cervone, G., 2015. "An analog ensemble for short-term probabilistic solar power forecast," Applied Energy, Elsevier, vol. 157(C), pages 95-110.
    20. Ben-Haim, Yakov, 2021. "Feedback for energy conservation: An info-gap approach," Energy, Elsevier, vol. 223(C).

    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:9:y:2016:i:9:p:666-:d:76499. 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.