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Inspection and Structural Health Monitoring techniques for Concentrated Solar Power plants

Author

Listed:
  • Papaelias, Mayorkinos
  • Cheng, Liang
  • Kogia, Maria
  • Mohimi, Abbas
  • Kappatos, Vassilios
  • Selcuk, Cem
  • Constantinou, Louis
  • Muñoz, Carlos Quiterio Gómez
  • Marquez, Fausto Pedro Garcia
  • Gan, Tat-Hean

Abstract

Parabolic trough concentrators are the most widely deployed type of solar thermal power plant. The majority of parabolic trough plants operate up to 400 °C. However, recent technological advances involving molten salts instead of oil as working fluid the maximum operating temperature can exceed 550 °C. CSP plants face several technical problems related to the structural integrity and inspection of critical components such as the solar receivers and insulated piping of the coolant system. The inspection of the absorber tube is very difficult as it is covered by a cermet coating and placed inside a glass envelope under vacuum. Volumetric solar receivers are used in solar tower designs enabling increased operational temperature and plant efficiency. However, volumetric solar receiver designs inherently pose a challenging inspection problem for maintenance engineers due to their very complex geometry and characteristics of the materials employed in their manufacturing. In addition, the rest of the coolant system is insulated to minimise heat losses and therefore it cannot be inspected unless the insulation has been removed beforehand. This paper discusses the non-destructive evaluation techniques that can be employed to inspect solar receivers and insulated pipes as well as relevant research and development work in this field.

Suggested Citation

  • Papaelias, Mayorkinos & Cheng, Liang & Kogia, Maria & Mohimi, Abbas & Kappatos, Vassilios & Selcuk, Cem & Constantinou, Louis & Muñoz, Carlos Quiterio Gómez & Marquez, Fausto Pedro Garcia & Gan, Tat-H, 2016. "Inspection and Structural Health Monitoring techniques for Concentrated Solar Power plants," Renewable Energy, Elsevier, vol. 85(C), pages 1178-1191.
    • Handle: RePEc:eee:renene:v:85:y:2016:i:c:p:1178-1191
    DOI: 10.1016/j.renene.2015.07.090
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    Citations

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    Cited by:

    1. Bijarniya, Jay Prakash & Sudhakar, K. & Baredar, Prashant, 2016. "Concentrated solar power technology in India: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 63(C), pages 593-603.
    2. Natraj, & Reddy, K.S., 2023. "Investigations of thermo-structural instability on the performance of solar parabolic trough collectors," Renewable Energy, Elsevier, vol. 202(C), pages 381-393.
    3. Fuqiang, Wang & Ziming, Cheng & Jianyu, Tan & Yuan, Yuan & Yong, Shuai & Linhua, Liu, 2017. "Progress in concentrated solar power technology with parabolic trough collector system: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1314-1328.
    4. Arcos Jiménez, Alfredo & Zhang, Long & Gómez Muñoz, Carlos Quiterio & García Márquez, Fausto Pedro, 2020. "Maintenance management based on Machine Learning and nonlinear features in wind turbines," Renewable Energy, Elsevier, vol. 146(C), pages 316-328.
    5. Pliego Marugán, Alberto & Peco Chacón, Ana María & García Márquez, Fausto Pedro, 2019. "Reliability analysis of detecting false alarms that employ neural networks: A real case study on wind turbines," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    6. Villada, Carolina & Bonk, Alexander & Bauer, Thomas & Bolívar, Francisco, 2018. "High-temperature stability of nitrate/nitrite molten salt mixtures under different atmospheres," Applied Energy, Elsevier, vol. 226(C), pages 107-115.
    7. Arcos Jiménez, Alfredo & Gómez Muñoz, Carlos Quiterio & García Márquez, Fausto Pedro, 2019. "Dirt and mud detection and diagnosis on a wind turbine blade employing guided waves and supervised learning classifiers," Reliability Engineering and System Safety, Elsevier, vol. 184(C), pages 2-12.
    8. Lamnatou, Chr. & Chemisana, D., 2017. "Concentrating solar systems: Life Cycle Assessment (LCA) and environmental issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 916-932.
    9. Jiménez, Alfredo Arcos & García Márquez, Fausto Pedro & Moraleda, Victoria Borja & Gómez Muñoz, Carlos Quiterio, 2019. "Linear and nonlinear features and machine learning for wind turbine blade ice detection and diagnosis," Renewable Energy, Elsevier, vol. 132(C), pages 1034-1048.
    10. Walczak, Magdalena & Pineda, Fabiola & Fernández, Ángel G. & Mata-Torres, Carlos & Escobar, Rodrigo A., 2018. "Materials corrosion for thermal energy storage systems in concentrated solar power plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 86(C), pages 22-44.
    11. Cheng, Liang & Kogia, Maria & Mohimi, Abbas & Kappatos, Vassilios & Selcuk, Cem & Gan, Tat-Hean, 2017. "Crack characterisation using invariable feature extraction in stainless steel specimen used for absorber tubes of CSP applications via EMAT," Renewable Energy, Elsevier, vol. 101(C), pages 771-781.

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