IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i7p2324-d777427.html
   My bibliography  Save this article

Monitoring the Geometry of Tall Objects in Energy Industry

Author

Listed:
  • Tadeusz Głowacki

    (Faculty of Geoengineering, Mining and Geology, Wroclaw University of Science and Technology, 27 Wyb. Wyspianskkiego St., 50-370 Wroclaw, Poland)

Abstract

The landscape shaped by the energy industry is rich in various slender structures, such as smokestacks, cooling towers, and others. It is thus becoming increasingly important to effectively monitor the geometrical condition of all types of such structures. Slender structures are deformed elastically under loads due to wind. A proper analysis of the changes and deformations of such structures requires a continuous ground-based measurement system which allows the movement of the structure to be measured in two horizontal directions, from a significant distance and with a possibly reduced number of stations. For this purpose, two methods were implemented: a linear terrestrial laser scanning method (TLS) and an optical, direct distance measurement method—tachymetry (TCH). The least squares method was used to fit rings on various levels of the structure and then the centers of the rings were identified. The comparison of the identified ring centers enabled the axis of the structure to be measured for deviation in two perpendicular directions. The methods were verified on actual structures: a smokestack 110 m in height, a cooling tower 60 m in height, and a wind turbine with the rotor axis at 149 m. The measurement results were compared with respect to the measurement time and the obtained accuracies at which the point locations were identified on the structure. The proposed methods are an effective tool for monitoring the condition of slender objects both during their operating life and after it. Regular monitoring of the geometric condition of slender structures in the energy industry limits the risk of major or catastrophic events, and as a result allows the safe and uninterrupted delivery of electric energy to clients.

Suggested Citation

  • Tadeusz Głowacki, 2022. "Monitoring the Geometry of Tall Objects in Energy Industry," Energies, MDPI, vol. 15(7), pages 1-15, March.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:7:p:2324-:d:777427
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/7/2324/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/7/2324/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dmitrii Bogdanov & Javier Farfan & Kristina Sadovskaia & Arman Aghahosseini & Michael Child & Ashish Gulagi & Ayobami Solomon Oyewo & Larissa Souza Noel Simas Barbosa & Christian Breyer, 2019. "Radical transformation pathway towards sustainable electricity via evolutionary steps," Nature Communications, Nature, vol. 10(1), pages 1-16, December.
    2. Wymore, Mathew L. & Van Dam, Jeremy E. & Ceylan, Halil & Qiao, Daji, 2015. "A survey of health monitoring systems for wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 976-990.
    3. Pieraccini, Massimiliano & Parrini, Filippo & Fratini, Matteo & Atzeni, Carlo & Spinelli, Paolo, 2008. "In-service testing of wind turbine towers using a microwave sensor," Renewable Energy, Elsevier, vol. 33(1), pages 13-21.
    4. Paula Helming & Axel von Freyberg & Michael Sorg & Andreas Fischer, 2021. "Wind Turbine Tower Deformation Measurement Using Terrestrial Laser Scanning on a 3.4 MW Wind Turbine," Energies, MDPI, vol. 14(11), pages 1-14, June.
    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. Andreas Baumann-Ouyang & Jemil Avers Butt & Matej Varga & Andreas Wieser, 2023. "MIMO-SAR Interferometric Measurements for Wind Turbine Tower Deformation Monitoring," Energies, MDPI, vol. 16(3), pages 1-20, February.
    2. Farfan, Javier & Lohrmann, Alena & Breyer, Christian, 2019. "Integration of greenhouse agriculture to the energy infrastructure as an alimentary solution," Renewable and Sustainable Energy Reviews, Elsevier, vol. 110(C), pages 368-377.
    3. Kim, Sunwoo & Choi, Yechan & Park, Joungho & Adams, Derrick & Heo, Seongmin & Lee, Jay H., 2024. "Multi-period, multi-timescale stochastic optimization model for simultaneous capacity investment and energy management decisions for hybrid Micro-Grids with green hydrogen production under uncertainty," Renewable and Sustainable Energy Reviews, Elsevier, vol. 190(PA).
    4. 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.
    5. Bogdanov, Dmitrii & Toktarova, Alla & Breyer, Christian, 2019. "Transition towards 100% renewable power and heat supply for energy intensive economies and severe continental climate conditions: Case for Kazakhstan," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    6. Hasret Sahin & A. A. Solomon & Arman Aghahosseini & Christian Breyer, 2024. "Systemwide energy return on investment in a sustainable transition towards net zero power systems," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    7. Caldera, Upeksha & Breyer, Christian, 2020. "Strengthening the global water supply through a decarbonised global desalination sector and improved irrigation systems," Energy, Elsevier, vol. 200(C).
    8. Jing-Li Fan & Zezheng Li & Xi Huang & Kai Li & Xian Zhang & Xi Lu & Jianzhong Wu & Klaus Hubacek & Bo Shen, 2023. "A net-zero emissions strategy for China’s power sector using carbon-capture utilization and storage," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    9. Polzin, Friedemann & Sanders, Mark & Serebriakova, Alexandra, 2021. "Finance in global transition scenarios: Mapping investments by technology into finance needs by source," Energy Economics, Elsevier, vol. 99(C).
    10. Lorin Jenkel & Stefan Jonas & Angela Meyer, 2023. "Privacy-Preserving Fleet-Wide Learning of Wind Turbine Conditions with Federated Learning," Energies, MDPI, vol. 16(17), pages 1-29, September.
    11. Rubert, T. & Zorzi, G. & Fusiek, G. & Niewczas, P. & McMillan, D. & McAlorum, J. & Perry, M., 2019. "Wind turbine lifetime extension decision-making based on structural health monitoring," Renewable Energy, Elsevier, vol. 143(C), pages 611-621.
    12. Ruiz de la Hermosa González-Carrato, Raúl & García Márquez, Fausto Pedro & Dimlaye, Vichaar, 2015. "Maintenance management of wind turbines structures via MFCs and wavelet transforms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 472-482.
    13. Igliński, Bartłomiej & Iglińska, Anna & Koziński, Grzegorz & Skrzatek, Mateusz & Buczkowski, Roman, 2016. "Wind energy in Poland – History, current state, surveys, Renewable Energy Sources Act, SWOT analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 19-33.
    14. 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.
    15. Yuhan Zhang & Yongbin Wang & Zhibin Chen & Chengzhi Hu & Jiuhui Qu, 2024. "Recovering nutrients and unblocking the cake layer of an electrochemical anaerobic membrane bioreactor," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    16. Burgaç, Alper & Yavuz, Hakan, 2019. "Fuzzy Logic based hybrid type control implementation of a heaving wave energy converter," Energy, Elsevier, vol. 170(C), pages 1202-1214.
    17. Graça Gomes, João & Medeiros Pinto, José & Xu, Huijin & Zhao, Changying & Hashim, Haslenda, 2020. "Modeling and planning of the electricity energy system with a high share of renewable supply for Portugal," Energy, Elsevier, vol. 211(C).
    18. Wei-Hua Hu & De-Hui Tang & Ming Wang & Jun-Le Liu & Zuo-Hua Li & Wei Lu & Jun Teng & Samir Said & Rolf. G. Rohrmann, 2020. "Resonance Monitoring of a Horizontal Wind Turbine by Strain-Based Automated Operational Modal Analysis," Energies, MDPI, vol. 13(3), pages 1-21, January.
    19. Keck, Felix & Jütte, Silke & Lenzen, Manfred & Li, Mengyu, 2022. "Assessment of two optimisation methods for renewable energy capacity expansion planning," Applied Energy, Elsevier, vol. 306(PA).
    20. Stetco, Adrian & Dinmohammadi, Fateme & Zhao, Xingyu & Robu, Valentin & Flynn, David & Barnes, Mike & Keane, John & Nenadic, Goran, 2019. "Machine learning methods for wind turbine condition monitoring: A review," Renewable Energy, Elsevier, vol. 133(C), pages 620-635.

    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:15:y:2022:i:7:p:2324-:d:777427. 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.