IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i6p1558-d152452.html
   My bibliography  Save this article

A Method for Load Classification and Energy Scheduling Optimization to Improve Load Reliability

Author

Listed:
  • Yinze Ren

    (School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China)

  • Hongbin Wu

    (School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China)

  • Hejun Yang

    (School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China)

  • Shihai Yang

    (State Grid Jiangsu Electric Power Co. Ltd., Nanjing 210024, China)

  • Zhixin Li

    (State Grid Jiangsu Electric Power Co. Ltd., Nanjing 210024, China)

Abstract

With the large amount of distributed generation in use, the structure of the distribution system is increasingly complex. Therefore, it is necessary to establish a method to improve load reliability. Based on the reliability model of distributed generation, this paper investigates the time sequential simulation of a wind/solar/storage combined power supply system under off-grid operation. After classifying the load by power supply region, the load weight coefficient is established, which modifies the reliability index of the load point and system. The modified expected energy not supplied (EENS) is adopted as the objective function, and the particle swarm optimization algorithm is used to solving the optimal energy scheduling for improving the load reliability. Finally, the load reliability is calculated with a hybrid method. Using the IEEE-RBTS Bus 6 system as an example, the correctness and validity of the proposed method are verified as an effective way to improve load reliability.

Suggested Citation

  • Yinze Ren & Hongbin Wu & Hejun Yang & Shihai Yang & Zhixin Li, 2018. "A Method for Load Classification and Energy Scheduling Optimization to Improve Load Reliability," Energies, MDPI, vol. 11(6), pages 1-19, June.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:6:p:1558-:d:152452
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/6/1558/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/6/1558/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hao Bai & Shihong Miao & Pipei Zhang & Zhan Bai, 2015. "Reliability Evaluation of a Distribution Network with Microgrid Based on a Combined Power Generation System," Energies, MDPI, vol. 8(2), pages 1-26, February.
    2. Haipeng Xie & Zhaohong Bie & Yanling Lin & Chao Zheng, 2017. "A Hybrid Reliability Evaluation Method for Meshed VSC-HVDC Grids," Energies, MDPI, vol. 10(7), pages 1-17, July.
    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. Yuval Beck & Ram Machlev, 2019. "Harmonic Loads Classification by Means of Currents’ Physical Components," Energies, MDPI, vol. 12(21), pages 1-18, October.
    2. Sana Iqbal & Mohammad Sarfraz & Mohammad Ayyub & Mohd Tariq & Ripon K. Chakrabortty & Michael J. Ryan & Basem Alamri, 2021. "A Comprehensive Review on Residential Demand Side Management Strategies in Smart Grid Environment," Sustainability, MDPI, vol. 13(13), pages 1, June.

    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. Bingke Yan & Bo Wang & Lin Zhu & Hesen Liu & Yilu Liu & Xingpei Ji & Dichen Liu, 2015. "A Novel, Stable, and Economic Power Sharing Scheme for an Autonomous Microgrid in the Energy Internet," Energies, MDPI, vol. 8(11), pages 1-24, November.
    2. Yi Liu & Zhanqing Yu & Haibo Li & Rong Zeng, 2019. "The LCOE-Indicator-Based Comprehensive Economic Comparison between AC and DC Power Distribution Networks with High Penetration of Renewable Energy," Energies, MDPI, vol. 12(24), pages 1-15, December.
    3. Feng Wang & Lizheng Sun & Zhang Wen & Fang Zhuo, 2022. "Overview of Inertia Enhancement Methods in DC System," Energies, MDPI, vol. 15(18), pages 1-25, September.
    4. Weipeng Yang & Aimin Zhang & Jungang Li & Guoqi Li & Hang Zhang & Jianhua Wang, 2017. "Integral Plus Resonant Sliding Mode Direct Power Control for VSC-HVDC Systems under Unbalanced Grid Voltage Conditions," Energies, MDPI, vol. 10(10), pages 1-17, October.
    5. Escalera, Alberto & Hayes, Barry & Prodanović, Milan, 2018. "A survey of reliability assessment techniques for modern distribution networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 344-357.
    6. Quddus, Md Abdul & Kabli, Mohannad & Marufuzzaman, Mohammad, 2019. "Modeling electric vehicle charging station expansion with an integration of renewable energy and Vehicle-to-Grid sources," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 251-279.
    7. Bo Pang & Heng Nian, 2019. "Improved Operation Strategy with Alternative Control Targets for Voltage Source Converter under Harmonically Distorted Grid Considering Inter-Harmonics," Energies, MDPI, vol. 12(7), pages 1-14, March.
    8. Qunli Wu & Chenyang Peng, 2016. "Comprehensive Benefit Evaluation of the Power Distribution Network Planning Project Based on Improved IAHP and Multi-Level Extension Assessment Method," Sustainability, MDPI, vol. 8(8), pages 1-18, August.
    9. Xin Li & Xiaodi Zhang & Yuling Fan, 2019. "A Two-Step Framework for Energy Local Area Network Scheduling Problem with Electric Vehicles Based on Global–Local Optimization Method," Energies, MDPI, vol. 12(1), pages 1-17, January.
    10. Andrés Felipe Pérez Posada & Juan G. Villegas & Jesús M. López-Lezama, 2017. "A Scatter Search Heuristic for the Optimal Location, Sizing and Contract Pricing of Distributed Generation in Electric Distribution Systems," Energies, MDPI, vol. 10(10), pages 1-16, September.
    11. Jichao Hong & Zhenpo Wang & Peng Liu, 2017. "Big-Data-Based Thermal Runaway Prognosis of Battery Systems for Electric Vehicles," Energies, MDPI, vol. 10(7), pages 1-16, July.
    12. Jose L. López-Prado & Jorge I. Vélez & Guisselle A. Garcia-Llinás, 2020. "Reliability Evaluation in Distribution Networks with Microgrids: Review and Classification of the Literature," Energies, MDPI, vol. 13(23), pages 1-31, November.

    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:11:y:2018:i:6:p:1558-:d:152452. 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.