IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v312y2022ics0306261922000757.html
   My bibliography  Save this article

Event-triggered distributed voltage regulation by heterogeneous BESS in low-voltage distribution networks

Author

Listed:
  • Kang, Wenfa
  • Chen, Minyou
  • Guan, Yajuan
  • Wei, Baoze
  • Vasquez Q., Juan C.
  • Guerrero, Josep M.

Abstract

High penetration level of PV sources in low-voltage distribution network (LVDN) leads to the voltage fluctuation problem, which may limit the maximal PV power generation due to the security issues of distribution networks. This paper proposes a distributed voltage regulation method by sharing the power of distributed heterogeneous battery energy storage systems (BESS) properly. With the help of local voltage/power droop controller, BESS absorbs power from LVDN when nodal voltage is above the upper limit, and injects power to LVDN when nodal voltage is lower than the bottom limit. The voltage regulation burden is properly shared among BESSs not only according to the capacities but also the state of charge (SoC). Moreover, even the communication network among BESSs is time-varying, the proposed method is able to regulate nodal voltages. For an extreme scenario with communication failures, the proposed method can also guarantee the voltage regulation and power sharing locally. Furthermore, a dynamic event-triggered communication strategy is designed for BESS aiming at reducing communication burden. Four simulation cases are designed on MATLAB/Simulink to validate the effectiveness of the proposed method. The results show that the proposed method is capable of maintaining nodal voltages within the normal range, and achieves the proportional regulation and SoC balance among different BESS with reduced communications.

Suggested Citation

  • Kang, Wenfa & Chen, Minyou & Guan, Yajuan & Wei, Baoze & Vasquez Q., Juan C. & Guerrero, Josep M., 2022. "Event-triggered distributed voltage regulation by heterogeneous BESS in low-voltage distribution networks," Applied Energy, Elsevier, vol. 312(C).
    • Handle: RePEc:eee:appene:v:312:y:2022:i:c:s0306261922000757
    DOI: 10.1016/j.apenergy.2022.118597
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261922000757
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2022.118597?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ali, Md Sawkat & Haque, Md Mejbaul & Wolfs, Peter, 2019. "A review of topological ordering based voltage rise mitigation methods for LV distribution networks with high levels of photovoltaic penetration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 463-476.
    2. Ma, Wei & Wang, Wei & Chen, Zhe & Wu, Xuezhi & Hu, Ruonan & Tang, Fen & Zhang, Weige, 2021. "Voltage regulation methods for active distribution networks considering the reactive power optimization of substations," Applied Energy, Elsevier, vol. 284(C).
    3. Zhang, Zhengfa & da Silva, Filipe Faria & Guo, Yifei & Bak, Claus Leth & Chen, Zhe, 2021. "Double-layer stochastic model predictive voltage control in active distribution networks with high penetration of renewables," Applied Energy, Elsevier, vol. 302(C).
    4. Wang, Xiaoxue & Wang, Chengshan & Xu, Tao & Guo, Lingxu & Li, Peng & Yu, Li & Meng, He, 2018. "Optimal voltage regulation for distribution networks with multi-microgrids," Applied Energy, Elsevier, vol. 210(C), pages 1027-1036.
    5. Li, Peng & Ji, Haoran & Yu, Hao & Zhao, Jinli & Wang, Chengshan & Song, Guanyu & Wu, Jianzhong, 2019. "Combined decentralized and local voltage control strategy of soft open points in active distribution networks," Applied Energy, Elsevier, vol. 241(C), pages 613-624.
    6. Wang, Xiaoxue & Wang, Chengshan & Xu, Tao & Meng, He & Li, Peng & Yu, Li, 2018. "Distributed voltage control for active distribution networks based on distribution phasor measurement units," Applied Energy, Elsevier, vol. 229(C), pages 804-813.
    7. Ji, Haoran & Wang, Chengshan & Li, Peng & Zhao, Jinli & Song, Guanyu & Ding, Fei & Wu, Jianzhong, 2018. "A centralized-based method to determine the local voltage control strategies of distributed generator operation in active distribution networks," Applied Energy, Elsevier, vol. 228(C), pages 2024-2036.
    8. Ng, Kong Soon & Moo, Chin-Sien & Chen, Yi-Ping & Hsieh, Yao-Ching, 2009. "Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries," Applied Energy, Elsevier, vol. 86(9), pages 1506-1511, September.
    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. Xiangdong Wang & Lei Wang & Wenfa Kang & Tiecheng Li & Hao Zhou & Xuekai Hu & Kai Sun, 2022. "Distributed Nodal Voltage Regulation Method for Low-Voltage Distribution Networks by Sharing PV System Reactive Power," Energies, MDPI, vol. 16(1), pages 1-15, December.
    2. Zhang, Zhaoyi & Shang, Lei & Liu, Chengxi & Lai, Qiupin & Jiang, Youjin, 2023. "Consensus-based distributed optimal power flow using gradient tracking technique for short-term power fluctuations," Energy, Elsevier, vol. 264(C).
    3. Kwang-Hoon Yoon & Joong-Woo Shin & Tea-Yang Nam & Jae-Chul Kim & Won-Sik Moon, 2022. "Operation Method of On-Load Tap Changer on Main Transformer Considering Reverse Power Flow in Distribution System Connected with High Penetration on Photovoltaic System," Energies, MDPI, vol. 15(17), pages 1-17, September.
    4. Zhenming Li & Yunfeng Yan & Donglian Qi & Shuo Yan & Minghao Wang, 2022. "Distributed Voltage Optimization Control of BESS in AC Distribution Networks with High PV Penetration," Energies, MDPI, vol. 15(11), pages 1-14, 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. Mak, Davye & Choeum, Daranith & Choi, Dae-Hyun, 2020. "Sensitivity analysis of volt-VAR optimization to data changes in distribution networks with distributed energy resources," Applied Energy, Elsevier, vol. 261(C).
    2. Zhu, Xingxu & Hou, Xiangchen & Li, Junhui & Yan, Gangui & Li, Cuiping & Wang, Dongbo, 2023. "Distributed online prediction optimization algorithm for distributed energy resources considering the multi-periods optimal operation," Applied Energy, Elsevier, vol. 348(C).
    3. Zhang, Bin & Hu, Weihao & Ghias, Amer M.Y.M. & Xu, Xiao & Chen, Zhe, 2022. "Multi-agent deep reinforcement learning-based coordination control for grid-aware multi-buildings," Applied Energy, Elsevier, vol. 328(C).
    4. Almasalma, Hamada & Claeys, Sander & Deconinck, Geert, 2019. "Peer-to-peer-based integrated grid voltage support function for smart photovoltaic inverters," Applied Energy, Elsevier, vol. 239(C), pages 1037-1048.
    5. A.S. Jameel Hassan & Umar Marikkar & G.W. Kasun Prabhath & Aranee Balachandran & W.G. Chaminda Bandara & Parakrama B. Ekanayake & Roshan I. Godaliyadda & Janaka B. Ekanayake, 2021. "A Sensitivity Matrix Approach Using Two-Stage Optimization for Voltage Regulation of LV Networks with High PV Penetration," Energies, MDPI, vol. 14(20), pages 1-24, October.
    6. Su, Hongzhi & Wang, Chengshan & Li, Peng & Li, Peng & Liu, Zhelin & Wu, Jianzhong, 2019. "Novel voltage-to-power sensitivity estimation for phasor measurement unit-unobservable distribution networks based on network equivalent," Applied Energy, Elsevier, vol. 250(C), pages 302-312.
    7. Tang, Chong & Liu, Mingbo & Dai, Yue & Wang, Zhijun & Xie, Min, 2019. "Decentralized saddle-point dynamics solution for optimal power flow of distribution systems with multi-microgrids," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    8. Ferreira, Willian M. & Meneghini, Ivan R. & Brandao, Danilo I. & Guimarães, Frederico G., 2020. "Preference cone based multi-objective evolutionary algorithm applied to optimal management of distributed energy resources in microgrids," Applied Energy, Elsevier, vol. 274(C).
    9. Wu, Wei & Li, Peng & Fu, Xiaopeng & Yan, Jinyue & Wang, Chengshan, 2022. "Flexible Shifted-Frequency analysis for Multi-Timescale simulations of active distribution networks," Applied Energy, Elsevier, vol. 321(C).
    10. Tsao, Yu-Chung & Beyene, Tsehaye Dedimas & Thanh, Vo-Van & Gebeyehu, Sisay Geremew & Kuo, Tsai-Chi, 2022. "Power distribution network design considering the distributed generations and differential and dynamic pricing," Energy, Elsevier, vol. 241(C).
    11. Wang, Licheng & Yan, Ruifeng & Saha, Tapan Kumar, 2019. "Voltage regulation challenges with unbalanced PV integration in low voltage distribution systems and the corresponding solution," Applied Energy, Elsevier, vol. 256(C).
    12. Shehzar Shahzad Sheikh & Mahnoor Anjum & Muhammad Abdullah Khan & Syed Ali Hassan & Hassan Abdullah Khalid & Adel Gastli & Lazhar Ben-Brahim, 2020. "A Battery Health Monitoring Method Using Machine Learning: A Data-Driven Approach," Energies, MDPI, vol. 13(14), pages 1-16, July.
    13. Yang, Duo & Wang, Yujie & Pan, Rui & Chen, Ruiyang & Chen, Zonghai, 2018. "State-of-health estimation for the lithium-ion battery based on support vector regression," Applied Energy, Elsevier, vol. 227(C), pages 273-283.
    14. Li, Peng & Ji, Haoran & Yu, Hao & Zhao, Jinli & Wang, Chengshan & Song, Guanyu & Wu, Jianzhong, 2019. "Combined decentralized and local voltage control strategy of soft open points in active distribution networks," Applied Energy, Elsevier, vol. 241(C), pages 613-624.
    15. Wenxian Duan & Chuanxue Song & Silun Peng & Feng Xiao & Yulong Shao & Shixin Song, 2020. "An Improved Gated Recurrent Unit Network Model for State-of-Charge Estimation of Lithium-Ion Battery," Energies, MDPI, vol. 13(23), pages 1-19, December.
    16. Ahmadi, Seyed Ehsan & Sadeghi, Delnia & Marzband, Mousa & Abusorrah, Abdullah & Sedraoui, Khaled, 2022. "Decentralized bi-level stochastic optimization approach for multi-agent multi-energy networked micro-grids with multi-energy storage technologies," Energy, Elsevier, vol. 245(C).
    17. Guoqing Jin & Lan Li & Yidan Xu & Minghui Hu & Chunyun Fu & Datong Qin, 2020. "Comparison of SOC Estimation between the Integer-Order Model and Fractional-Order Model Under Different Operating Conditions," Energies, MDPI, vol. 13(7), pages 1-17, April.
    18. Lu, Yu & Xiang, Yue & Huang, Yuan & Yu, Bin & Weng, Liguo & Liu, Junyong, 2023. "Deep reinforcement learning based optimal scheduling of active distribution system considering distributed generation, energy storage and flexible load," Energy, Elsevier, vol. 271(C).
    19. Hu, Lin & Hu, Xiaosong & Che, Yunhong & Feng, Fei & Lin, Xianke & Zhang, Zhiyong, 2020. "Reliable state of charge estimation of battery packs using fuzzy adaptive federated filtering," Applied Energy, Elsevier, vol. 262(C).
    20. Berecibar, M. & Gandiaga, I. & Villarreal, I. & Omar, N. & Van Mierlo, J. & Van den Bossche, P., 2016. "Critical review of state of health estimation methods of Li-ion batteries for real applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 572-587.

    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:eee:appene:v:312:y:2022:i:c:s0306261922000757. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.