IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i13p4891-d1177378.html
   My bibliography  Save this article

A Modular Algorithm Based on the Minimum-Cost-Path Problem for Optimizing LTC Operations in Photovoltaic Integrated Distribution Systems

Author

Listed:
  • Arbel Yaniv

    (Department of Physical Electronics, School of Electrical Engineering, Faculty of Engineering, Tel Aviv University, Tel-Aviv 69978, Israel)

  • Yuval Beck

    (Department of Physical Electronics, School of Electrical Engineering, Faculty of Engineering, Tel Aviv University, Tel-Aviv 69978, Israel)

Abstract

This paper presents a novel modular voltage control algorithm for optimal scheduling of a distribution system’s load tap changers to minimize the number of tap changes while maintaining a voltage deviation (VD) around a desired target. To this end, a bi-objective optimal voltage regulation (OVR) problem is addressed in two distinct stages. First, the operational constraint on the load tap changer is removed to form a single-objective OVR problem relating to the voltage. The solution obtained in this stage is ultimately utilized to determine the penalty value assigned to the distance from the optimal (solely in terms of voltage) control value. In the second stage, the optimal scheduling problem is formulated as a minimum-cost-path problem, which can be efficiently solved via dynamic programming. This approach allows the identification of optimal scheduling that considers both the voltage-related objective as well as the number of load tap changer switching operations with no added computational burden beyond that of a simple voltage optimization problem. The method imposes no restriction on the load tap changer’s operation and is tested under two different target functions on the standard IEEE-123 test case. The first attains a nominal voltage with a 0.056 p.u. voltage deviation and the second is the well-known conservation voltage reduction (CVR) case with a 0.17 p.u. voltage deviation. The method is compared to an evolutionary-based algorithm and shows significant improvement in the voltage deviation by a factor of 3.5 as well as a computation time acceleration of two orders of magnitude. The paper demonstrates the effectiveness and potential of the proposed method as a key feature in future cutting-edge OVR methods.

Suggested Citation

  • Arbel Yaniv & Yuval Beck, 2023. "A Modular Algorithm Based on the Minimum-Cost-Path Problem for Optimizing LTC Operations in Photovoltaic Integrated Distribution Systems," Energies, MDPI, vol. 16(13), pages 1-18, June.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:13:p:4891-:d:1177378
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/13/4891/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/13/4891/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zou, Bin & Peng, Jinqing & Li, Sihui & Li, Yi & Yan, Jinyue & Yang, Hongxing, 2022. "Comparative study of the dynamic programming-based and rule-based operation strategies for grid-connected PV-battery systems of office buildings," Applied Energy, Elsevier, vol. 305(C).
    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. Gao, Datong & Zhao, Bin & Kwan, Trevor Hocksun & Hao, Yong & Pei, Gang, 2022. "The spatial and temporal mismatch phenomenon in solar space heating applications: status and solutions," Applied Energy, Elsevier, vol. 321(C).
    2. Yazhou Zhao & Xiangxi Qin & Xiangyu Shi, 2022. "A Comprehensive Evaluation Model on Optimal Operational Schedules for Battery Energy Storage System by Maximizing Self-Consumption Strategy and Genetic Algorithm," Sustainability, MDPI, vol. 14(14), pages 1-34, July.
    3. Baohong Jin & Zhichao Liu & Yichuan Liao, 2023. "Exploring the Impact of Regional Integrated Energy Systems Performance by Energy Storage Devices Based on a Bi-Level Dynamic Optimization Model," Energies, MDPI, vol. 16(6), pages 1-21, March.
    4. Javed, Muhammad Shahzad & Jurasz, Jakub & McPherson, Madeleine & Dai, Yanjun & Ma, Tao, 2022. "Quantitative evaluation of renewable-energy-based remote microgrids: curtailment, load shifting, and reliability," Renewable and Sustainable Energy Reviews, Elsevier, vol. 164(C).
    5. Baigali Erdenebat & Naomitsu Urasaki & Sergelen Byambaa, 2022. "A Strategy for Grid-Connected PV-Battery System of Mongolian Ger," Energies, MDPI, vol. 15(5), pages 1-13, March.
    6. Zhou, Xinlei & Xue, Shan & Du, Han & Ma, Zhenjun, 2023. "Optimization of building demand flexibility using reinforcement learning and rule-based expert systems," Applied Energy, Elsevier, vol. 350(C).
    7. Ma, Tao & Zhang, Yijie & Gu, Wenbo & Xiao, Gang & Yang, Hongxing & Wang, Shuxiao, 2022. "Strategy comparison and techno-economic evaluation of a grid-connected photovoltaic-battery system," Renewable Energy, Elsevier, vol. 197(C), pages 1049-1060.
    8. Zhang, Yijie & Ma, Tao & Yang, Hongxing, 2022. "Grid-connected photovoltaic battery systems: A comprehensive review and perspectives," Applied Energy, Elsevier, vol. 328(C).
    9. Asmita Ajay Rathod & Balaji Subramanian, 2022. "Scrutiny of Hybrid Renewable Energy Systems for Control, Power Management, Optimization and Sizing: Challenges and Future Possibilities," Sustainability, MDPI, vol. 14(24), pages 1-35, December.
    10. Liao, Wei & Xiao, Fu & Li, Yanxue & Peng, Jinqing, 2024. "Comparative study on electricity transactions between multi-microgrid: A hybrid game theory-based peer-to-peer trading in heterogeneous building communities considering electric vehicles," Applied Energy, Elsevier, vol. 367(C).
    11. Liao, Wei & Xiao, Fu & Li, Yanxue & Zhang, Hanbei & Peng, Jinqing, 2024. "A comparative study of demand-side energy management strategies for building integrated photovoltaics-battery and electric vehicles (EVs) in diversified building communities," Applied Energy, Elsevier, vol. 361(C).
    12. Jahangir Hossain & Aida. F. A. Kadir & Hussain Shareef & Rampelli Manojkumar & Nagham Saeed & Ainain. N. Hanafi, 2023. "A Grid-Connected Optimal Hybrid PV-BES System Sizing for Malaysian Commercial Buildings," Sustainability, MDPI, vol. 15(13), pages 1-20, July.
    13. Li, Houpei & Li, Jun & Li, Sihui & Peng, Jinqing & Ji, Jie & Yan, Jinyue, 2023. "Matching characteristics and AC performance of the photovoltaic-driven air conditioning system," Energy, Elsevier, vol. 264(C).
    14. Baigali Erdenebat & Davaanyam Buyankhishig & Sergelen Byambaa & Naomitsu Urasaki, 2023. "A Study of Grid-Connected Residential PV-Battery Systems in Mongolia," Energies, MDPI, vol. 16(10), pages 1-14, May.
    15. Ouédraogo, S. & Faggianelli, G.A. & Notton, G. & Duchaud, J.L. & Voyant, C., 2022. "Impact of electricity tariffs and energy management strategies on PV/Battery microgrid performances," Renewable Energy, Elsevier, vol. 199(C), pages 816-825.
    16. Li, Sihui & Peng, Jinqing & Li, Houpei & Zou, Bin & Song, Jiaming & Ma, Tao & Ji, Jie, 2022. "Zero energy potential of PV direct-driven air conditioners coupled with phase change materials and load flexibility," Renewable Energy, Elsevier, vol. 200(C), pages 419-432.
    17. Wu, Yaling & Liu, Zhongbing & Li, Benjia & Liu, Jiangyang & Zhang, Ling, 2022. "Energy management strategy and optimal battery capacity for flexible PV-battery system under time-of-use tariff," Renewable Energy, Elsevier, vol. 200(C), pages 558-570.
    18. Sun, Chu & Ali, Syed Qaseem & Joos, Geza & Paquin, Jean-Nicolas & Montenegro, Juan Felipe Patarroyo, 2023. "Design and CHIL testing of microgrid controller with general rule-based dispatch," Applied Energy, Elsevier, vol. 345(C).
    19. Guo, Jiacheng & Liu, Zhijian & Wu, Xuan & Wu, Di & Zhang, Shicong & Yang, Xinyan & Ge, Hua & Zhang, Peiwen, 2022. "Two-layer co-optimization method for a distributed energy system combining multiple energy storages," Applied Energy, Elsevier, vol. 322(C).
    20. An, Su & Wang, Honglei & Leng, Xiaoxia, 2022. "Optimal operation of multi-micro energy grids under distribution network in Southwest China," Applied Energy, Elsevier, vol. 309(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:16:y:2023:i:13:p:4891-:d:1177378. 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.