IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v306y2022ipbs0306261921013519.html
   My bibliography  Save this article

A group sparse Bayesian learning algorithm for harmonic state estimation in power systems

Author

Listed:
  • Zhou, Wei
  • Wu, Yue
  • Huang, Xiang
  • Lu, Renzhi
  • Zhang, Hai-Tao

Abstract

In view of increasing concerns about climate change and global warming, various renewable energy sources are widely adopted in power systems to reduce greenhouse gas emissions. However, the widespread adoption of renewable energy sources exacerbates the problem of harmonics pollution. In order to improve power quality, it is urgent to develop a new approach for monitoring harmonics. By leveraging the structured sparsity and spatial sparsity of harmonic sources, this paper proposes a group sparse Bayesian learning method for solving harmonic state estimation problems. The proposed algorithm can employ a small number of measurements less than the number of state variables to pinpoint harmonic sources and to estimate the harmonic magnitudes and angles. Moreover, the proposed method achieves automatic hyperparameter adjustments and solves the system states in complex domain without splitting them into real and imaginary parts. Extensive results on a benchmark IEEE 14-bus system are presented to substantiate the superiority of the proposed method in terms of localization accuracy and harmonic magnitude and phase angle estimation.

Suggested Citation

  • Zhou, Wei & Wu, Yue & Huang, Xiang & Lu, Renzhi & Zhang, Hai-Tao, 2022. "A group sparse Bayesian learning algorithm for harmonic state estimation in power systems," Applied Energy, Elsevier, vol. 306(PB).
    • Handle: RePEc:eee:appene:v:306:y:2022:i:pb:s0306261921013519
    DOI: 10.1016/j.apenergy.2021.118063
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261921013519
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2021.118063?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. Yang, Ting & Pen, Haibo & Wang, Dan & Wang, Zhaoxia, 2016. "Harmonic analysis in integrated energy system based on compressed sensing," Applied Energy, Elsevier, vol. 165(C), pages 583-591.
    2. Hannan, M.A. & Lipu, M.S. Hossain & Ker, Pin Jern & Begum, R.A. & Agelidis, Vasilios G. & Blaabjerg, F., 2019. "Power electronics contribution to renewable energy conversion addressing emission reduction: Applications, issues, and recommendations," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    3. Sun, Yuanyuan & Xie, Xiangmin & Wang, Qingyan & Zhang, Linghan & Li, Yahui & Jin, Zongshuai, 2020. "A bottom-up approach to evaluate the harmonics and power of home appliances in residential areas," Applied Energy, Elsevier, vol. 259(C).
    4. Adefarati, T. & Bansal, R.C., 2019. "Reliability, economic and environmental analysis of a microgrid system in the presence of renewable energy resources," Applied Energy, Elsevier, vol. 236(C), pages 1089-1114.
    5. Bogdanov, Dmitrii & Gulagi, Ashish & Fasihi, Mahdi & Breyer, Christian, 2021. "Full energy sector transition towards 100% renewable energy supply: Integrating power, heat, transport and industry sectors including desalination," Applied Energy, Elsevier, vol. 283(C).
    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. Md Jakir Hossain & Mia Naeini, 2022. "Multi-Area Distributed State Estimation in Smart Grids Using Data-Driven Kalman Filters," Energies, MDPI, vol. 15(19), pages 1-17, September.
    2. Ahmadreza Eslami & Michael Negnevitsky & Evan Franklin & Sarah Lyden, 2022. "Harmonic Source Location and Characterization Based on Permissible Current Limits by Using Deep Learning and Image Processing," Energies, MDPI, vol. 15(24), pages 1-21, December.

    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. Oyewo, Ayobami Solomon & Solomon, A.A. & Bogdanov, Dmitrii & Aghahosseini, Arman & Mensah, Theophilus Nii Odai & Ram, Manish & Breyer, Christian, 2021. "Just transition towards defossilised energy systems for developing economies: A case study of Ethiopia," Renewable Energy, Elsevier, vol. 176(C), pages 346-365.
    2. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    3. Lund, Henrik & Thellufsen, Jakob Zinck & Sorknæs, Peter & Mathiesen, Brian Vad & Chang, Miguel & Madsen, Poul Thøis & Kany, Mikkel Strunge & Skov, Iva Ridjan, 2022. "Smart energy Denmark. A consistent and detailed strategy for a fully decarbonized society," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    4. Łukasz Jarosław Kozar & Robert Matusiak & Marta Paduszyńska & Adam Sulich, 2022. "Green Jobs in the EU Renewable Energy Sector: Quantile Regression Approach," Energies, MDPI, vol. 15(18), pages 1-21, September.
    5. Md. Mosaraf Hossain Khan & Amran Hossain & Aasim Ullah & Molla Shahadat Hossain Lipu & S. M. Shahnewaz Siddiquee & M. Shafiul Alam & Taskin Jamal & Hafiz Ahmed, 2021. "Integration of Large-Scale Electric Vehicles into Utility Grid: An Efficient Approach for Impact Analysis and Power Quality Assessment," Sustainability, MDPI, vol. 13(19), pages 1-18, October.
    6. David Firnando Silalahi & Andrew Blakers & Cheng Cheng, 2023. "100% Renewable Electricity in Indonesia," Energies, MDPI, vol. 17(1), pages 1-22, December.
    7. Qingshan Gong & Yurong Xiong & Zhigang Jiang & Xugang Zhang & Mingmao Hu & Zhanlong Cao, 2022. "Economic, Environmental and Social Benefits Analysis of Remanufacturing Strategies for Used Products," Mathematics, MDPI, vol. 10(21), pages 1-20, October.
    8. Mehar Ullah & Daniel Gutierrez-Rojas & Eero Inkeri & Tero Tynjälä & Pedro H. J. Nardelli, 2022. "Operation of Power-to-X-Related Processes Based on Advanced Data-Driven Methods: A Comprehensive Review," Energies, MDPI, vol. 15(21), pages 1-17, October.
    9. Nguyen, Hai Tra & Safder, Usman & Nhu Nguyen, X.Q. & Yoo, ChangKyoo, 2020. "Multi-objective decision-making and optimal sizing of a hybrid renewable energy system to meet the dynamic energy demands of a wastewater treatment plant," Energy, Elsevier, vol. 191(C).
    10. Millinger, M. & Reichenberg, L. & Hedenus, F. & Berndes, G. & Zeyen, E. & Brown, T., 2022. "Are biofuel mandates cost-effective? - An analysis of transport fuels and biomass usage to achieve emissions targets in the European energy system," Applied Energy, Elsevier, vol. 326(C).
    11. Mohseni, Soheil & Brent, Alan C. & Burmester, Daniel, 2020. "A comparison of metaheuristics for the optimal capacity planning of an isolated, battery-less, hydrogen-based micro-grid," Applied Energy, Elsevier, vol. 259(C).
    12. Rafi Zahedi & Parisa Ranjbaran & Gevork B. Gharehpetian & Fazel Mohammadi & Roya Ahmadiahangar, 2021. "Cleaning of Floating Photovoltaic Systems: A Critical Review on Approaches from Technical and Economic Perspectives," Energies, MDPI, vol. 14(7), pages 1-25, April.
    13. Jovet, Yoann & Lefèvre, Frédéric & Laurent, Alexis & Clausse, Marc, 2022. "Combined energetic, economic and climate change assessment of heat pumps for industrial waste heat recovery," Applied Energy, Elsevier, vol. 313(C).
    14. Stöckl, Fabian & Schill, Wolf-Peter & Zerrahn, Alexander, 2021. "Optimal supply chains and power sector benefits of green hydrogen," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 11.
    15. Tsao, Yu-Chung & Thanh, Vo-Van, 2021. "Toward sustainable microgrids with blockchain technology-based peer-to-peer energy trading mechanism: A fuzzy meta-heuristic approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 136(C).
    16. Ram, Manish & Gulagi, Ashish & Aghahosseini, Arman & Bogdanov, Dmitrii & Breyer, Christian, 2022. "Energy transition in megacities towards 100% renewable energy: A case for Delhi," Renewable Energy, Elsevier, vol. 195(C), pages 578-589.
    17. Nor Liza Tumeran & Siti Hajar Yusoff & Teddy Surya Gunawan & Mohd Shahrin Abu Hanifah & Suriza Ahmad Zabidi & Bernardi Pranggono & Muhammad Sharir Fathullah Mohd Yunus & Siti Nadiah Mohd Sapihie & Asm, 2023. "Model Predictive Control Based Energy Management System Literature Assessment for RES Integration," Energies, MDPI, vol. 16(8), pages 1-27, April.
    18. Liu, Baonan & Zhou, Jianzhong & Xu, Yanhe & Lai, Xinjie & Shi, Yousong & Li, Mengyao, 2022. "An optimization decision-making framework for the optimal operation strategy of pumped storage hydropower system under extreme conditions," Renewable Energy, Elsevier, vol. 182(C), pages 254-273.
    19. Haas, Jannik & Prieto-Miranda, Luis & Ghorbani, Narges & Breyer, Christian, 2022. "Revisiting the potential of pumped-hydro energy storage: A method to detect economically attractive sites," Renewable Energy, Elsevier, vol. 181(C), pages 182-193.
    20. Shaheer Ansari & Afida Ayob & Molla Shahadat Hossain Lipu & Aini Hussain & Mohamad Hanif Md Saad, 2021. "Data-Driven Remaining Useful Life Prediction for Lithium-Ion Batteries Using Multi-Charging Profile Framework: A Recurrent Neural Network Approach," Sustainability, MDPI, vol. 13(23), pages 1-25, December.

    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:306:y:2022:i:pb:s0306261921013519. 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.