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Condition monitoring of wind turbines: Techniques and methods

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  1. Yang, Chunzhen & Liu, Jingquan & Zeng, Yuyun & Xie, Guangyao, 2019. "Real-time condition monitoring and fault detection of components based on machine-learning reconstruction model," Renewable Energy, Elsevier, vol. 133(C), pages 433-441.
  2. Li, Jianlan & Zhang, Xuran & Zhou, Xing & Lu, Luyi, 2019. "Reliability assessment of wind turbine bearing based on the degradation-Hidden-Markov model," Renewable Energy, Elsevier, vol. 132(C), pages 1076-1087.
  3. Thé, Jesse & Yu, Hesheng, 2017. "A critical review on the simulations of wind turbine aerodynamics focusing on hybrid RANS-LES methods," Energy, Elsevier, vol. 138(C), pages 257-289.
  4. Chen, Xuejun & Yang, Yongming & Cui, Zhixin & Shen, Jun, 2019. "Vibration fault diagnosis of wind turbines based on variational mode decomposition and energy entropy," Energy, Elsevier, vol. 174(C), pages 1100-1109.
  5. Yang, Xiyun & Zhang, Yanfeng & Lv, Wei & Wang, Dong, 2021. "Image recognition of wind turbine blade damage based on a deep learning model with transfer learning and an ensemble learning classifier," Renewable Energy, Elsevier, vol. 163(C), pages 386-397.
  6. Márquez, Fausto Pedro García & Pérez, Jesús María Pinar & Marugán, Alberto Pliego & Papaelias, Mayorkinos, 2016. "Identification of critical components of wind turbines using FTA over the time," Renewable Energy, Elsevier, vol. 87(P2), pages 869-883.
  7. Seyed Mojtaba Tabatabaeipour & Peter F. Odgaard & Thomas Bak & Jakob Stoustrup, 2012. "Fault Detection of Wind Turbines with Uncertain Parameters: A Set-Membership Approach," Energies, MDPI, vol. 5(7), pages 1-25, July.
  8. 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.
  9. Beganovic, Nejra & Söffker, Dirk, 2016. "Structural health management utilization for lifetime prognosis and advanced control strategy deployment of wind turbines: An overview and outlook concerning actual methods, tools, and obtained result," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 68-83.
  10. Segovia Ramírez, Isaac & Pliego Marugán, Alberto & García Márquez, Fausto Pedro, 2022. "A novel approach to optimize the positioning and measurement parameters in photovoltaic aerial inspections," Renewable Energy, Elsevier, vol. 187(C), pages 371-389.
  11. Zappalá, D. & Sarma, N. & Djurović, S. & Crabtree, C.J. & Mohammad, A. & Tavner, P.J., 2019. "Electrical & mechanical diagnostic indicators of wind turbine induction generator rotor faults," Renewable Energy, Elsevier, vol. 131(C), pages 14-24.
  12. Dao, Phong B., 2022. "On Wilcoxon rank sum test for condition monitoring and fault detection of wind turbines," Applied Energy, Elsevier, vol. 318(C).
  13. Papatheou, Evangelos & Dervilis, Nikolaos & Maguire, Andrew E. & Campos, Carles & Antoniadou, Ifigeneia & Worden, Keith, 2017. "Performance monitoring of a wind turbine using extreme function theory," Renewable Energy, Elsevier, vol. 113(C), pages 1490-1502.
  14. Hsu-Hao Yang & Mei-Ling Huang & Shih-Wei Yang, 2015. "Integrating Auto-Associative Neural Networks with Hotelling T 2 Control Charts for Wind Turbine Fault Detection," Energies, MDPI, vol. 8(10), pages 1-16, October.
  15. Zuojun Liu & Cheng Xiao & Tieling Zhang & Xu Zhang, 2020. "Research on Fault Detection for Three Types of Wind Turbine Subsystems Using Machine Learning," Energies, MDPI, vol. 13(2), pages 1-21, January.
  16. Habibi, Hamed & Howard, Ian & Simani, Silvio, 2019. "Reliability improvement of wind turbine power generation using model-based fault detection and fault tolerant control: A review," Renewable Energy, Elsevier, vol. 135(C), pages 877-896.
  17. Wolf-Gerrit Früh, 2023. "Assessing the Performance of Small Wind Energy Systems Using Regional Weather Data," Energies, MDPI, vol. 16(8), pages 1-21, April.
  18. 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.
  19. Walgern, Julia & Peters, Lennart & Madlener, Reinhard, 2017. "Economic Evaluation of Maintenance Strategies for Offshore Wind Turbines Based on Condition Monitoring Systems," FCN Working Papers 8/2017, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
  20. Xiaoxun, Zhu & Xinyu, Hang & Xiaoxia, Gao & Xing, Yang & Zixu, Xu & Yu, Wang & Huaxin, Liu, 2022. "Research on crack detection method of wind turbine blade based on a deep learning method," Applied Energy, Elsevier, vol. 328(C).
  21. Mengnan Cao & Yingning Qiu & Yanhui Feng & Hao Wang & Dan Li, 2016. "Study of Wind Turbine Fault Diagnosis Based on Unscented Kalman Filter and SCADA Data," Energies, MDPI, vol. 9(10), pages 1-18, October.
  22. Li, He & Teixeira, Angelo P. & Guedes Soares, C., 2020. "A two-stage Failure Mode and Effect Analysis of offshore wind turbines," Renewable Energy, Elsevier, vol. 162(C), pages 1438-1461.
  23. Zhao, Hongshan & Liu, Huihai & Hu, Wenjing & Yan, Xihui, 2018. "Anomaly detection and fault analysis of wind turbine components based on deep learning network," Renewable Energy, Elsevier, vol. 127(C), pages 825-834.
  24. Jijian Lian & Ou Cai & Xiaofeng Dong & Qi Jiang & Yue Zhao, 2019. "Health Monitoring and Safety Evaluation of the Offshore Wind Turbine Structure: A Review and Discussion of Future Development," Sustainability, MDPI, vol. 11(2), pages 1-29, January.
  25. Guo, Jihong & Liu, Chao & Cao, Jinfeng & Jiang, Dongxiang, 2021. "Damage identification of wind turbine blades with deep convolutional neural networks," Renewable Energy, Elsevier, vol. 174(C), pages 122-133.
  26. Goh, H.H. & Lee, S.W. & Chua, Q.S. & Goh, K.C. & Kok, B.C. & Teo, K.T.K., 2014. "Renewable energy project: Project management, challenges and risk," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 917-932.
  27. Rodríguez-López, Miguel A. & López-González, Luis M. & López-Ochoa, Luis M. & Las-Heras-Casas, Jesús, 2016. "Development of indicators for the detection of equipment malfunctions and degradation estimation based on digital signals (alarms and events) from operation SCADA," Renewable Energy, Elsevier, vol. 99(C), pages 224-236.
  28. Yang, Hsu-Hao & Huang, Mei-Ling & Lai, Chun-Mei & Jin, Jhih-Rong, 2018. "An approach combining data mining and control charts-based model for fault detection in wind turbines," Renewable Energy, Elsevier, vol. 115(C), pages 808-816.
  29. Jürgen Herp & Niels L. Pedersen & Esmaeil S. Nadimi, 2019. "Assessment of Early Stopping through Statistical Health Prognostic Models for Empirical RUL Estimation in Wind Turbine Main Bearing Failure Monitoring," Energies, MDPI, vol. 13(1), pages 1-18, December.
  30. Mohamed Benbouzid & Tarek Berghout & Nur Sarma & Siniša Djurović & Yueqi Wu & Xiandong Ma, 2021. "Intelligent Condition Monitoring of Wind Power Systems: State of the Art Review," Energies, MDPI, vol. 14(18), pages 1-33, September.
  31. Giovanni Gravito de Carvalho Chrysostomo & Marco Vinicius Bhering de Aguiar Vallim & Leilton Santos da Silva & Leandro A. Silva & Arnaldo Rabello de Aguiar Vallim Filho, 2020. "A Framework for Big Data Analytical Process and Mapping—BAProM: Description of an Application in an Industrial Environment," Energies, MDPI, vol. 13(22), pages 1-28, November.
  32. Shin, Dongheon & Ko, Kyungnam, 2017. "Comparative analysis of degradation rates for inland and seaside wind turbines in compliance with the International Electrotechnical Commission standard," Energy, Elsevier, vol. 118(C), pages 1180-1186.
  33. Zhou, H.F. & Zheng, J.F. & Xie, Z.L. & Lu, L.J. & Ni, Y.Q. & Ko, J.M., 2017. "Temperature effects on vision measurement system in long-term continuous monitoring of displacement," Renewable Energy, Elsevier, vol. 114(PB), pages 968-983.
  34. Li, Yanting & Wu, Zhenyu, 2020. "A condition monitoring approach of multi-turbine based on VAR model at farm level," Renewable Energy, Elsevier, vol. 166(C), pages 66-80.
  35. Marugán, Alberto Pliego & Márquez, Fausto Pedro García & Perez, Jesus María Pinar & Ruiz-Hernández, Diego, 2018. "A survey of artificial neural network in wind energy systems," Applied Energy, Elsevier, vol. 228(C), pages 1822-1836.
  36. Dao, Phong B., 2022. "Condition monitoring and fault diagnosis of wind turbines based on structural break detection in SCADA data," Renewable Energy, Elsevier, vol. 185(C), pages 641-654.
  37. Jichuan Kang & Zihao Wang & C. Guedes Soares, 2020. "Condition-Based Maintenance for Offshore Wind Turbines Based on Support Vector Machine," Energies, MDPI, vol. 13(14), pages 1-17, July.
  38. Faiz, Jawad & Moosavi, S.M.M., 2016. "Eccentricity fault detection – From induction machines to DFIG—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 169-179.
  39. Miguel A. Rodríguez-López & Luis M. López-González & Luis M. López-Ochoa & Jesús Las-Heras-Casas, 2018. "Methodology for Detecting Malfunctions and Evaluating the Maintenance Effectiveness in Wind Turbine Generator Bearings Using Generic versus Specific Models from SCADA Data," Energies, MDPI, vol. 11(4), pages 1-22, March.
  40. Hongsheng Su & Yifan Zhao & Xueqian Wang, 2023. "Analysis of a State Degradation Model and Preventive Maintenance Strategies for Wind Turbine Generators Based on Stochastic Differential Equations," Mathematics, MDPI, vol. 11(12), pages 1-20, June.
  41. Bon-Yong Koo & Dae-Yi Jung, 2019. "A Comparative Study on Primary Bearing Rating Life of a 5-MW Two-Blade Wind Turbine System Based on Two Different Control Domains," Energies, MDPI, vol. 12(13), pages 1-16, July.
  42. Igba, Joel & Alemzadeh, Kazem & Durugbo, Christopher & Eiriksson, Egill Thor, 2016. "Analysing RMS and peak values of vibration signals for condition monitoring of wind turbine gearboxes," Renewable Energy, Elsevier, vol. 91(C), pages 90-106.
  43. Milu Zhang & Tianzhen Wang & Tianhao Tang & Zhuo Liu & Christophe Claramunt, 2019. "A Synchronous Sampling Based Harmonic Analysis Strategy for Marine Current Turbine Monitoring System under Strong Interference Conditions," Energies, MDPI, vol. 12(11), pages 1-13, June.
  44. Bakir, I. & Yildirim, M. & Ursavas, E., 2021. "An integrated optimization framework for multi-component predictive analytics in wind farm operations & maintenance," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
  45. Enevoldsen, Peter, 2016. "Onshore wind energy in Northern European forests: Reviewing the risks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1251-1262.
  46. Pere Marti-Puig & Alejandro Blanco-M & Juan José Cárdenas & Jordi Cusidó & Jordi Solé-Casals, 2019. "Feature Selection Algorithms for Wind Turbine Failure Prediction," Energies, MDPI, vol. 12(3), pages 1-18, January.
  47. Esu, O.O. & Lloyd, S.D. & Flint, J.A. & Watson, S.J., 2016. "Feasibility of a fully autonomous wireless monitoring system for a wind turbine blade," Renewable Energy, Elsevier, vol. 97(C), pages 89-96.
  48. Sungmok Hwang & Cheol Yoo, 2021. "Health Monitoring and Diagnosis System for a Small H-Type Darrieus Vertical-Axis Wind Turbine," Energies, MDPI, vol. 14(21), pages 1-18, November.
  49. Rodrigo Barbosa de Santis & Marcelo Azevedo Costa, 2020. "Extended Isolation Forests for Fault Detection in Small Hydroelectric Plants," Sustainability, MDPI, vol. 12(16), pages 1-16, August.
  50. Pliego Marugán, Alberto & García Márquez, Fausto Pedro & Pinar Pérez, Jesús María, 2022. "A techno-economic model for avoiding conflicts of interest between owners of offshore wind farms and maintenance suppliers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
  51. Peng Guo & Jian Fu & XiYun Yang, 2018. "Condition Monitoring and Fault Diagnosis of Wind Turbines Gearbox Bearing Temperature Based on Kolmogorov-Smirnov Test and Convolutional Neural Network Model," Energies, MDPI, vol. 11(9), pages 1-16, August.
  52. Cambron, P. & Lepvrier, R. & Masson, C. & Tahan, A. & Pelletier, F., 2016. "Power curve monitoring using weighted moving average control charts," Renewable Energy, Elsevier, vol. 94(C), pages 126-135.
  53. Liu, W.Y. & Tang, B.P. & Han, J.G. & Lu, X.N. & Hu, N.N. & He, Z.Z., 2015. "The structure healthy condition monitoring and fault diagnosis methods in wind turbines: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 466-472.
  54. Ahmed Raza & Vladimir Ulansky, 2019. "Optimal Preventive Maintenance of Wind Turbine Components with Imperfect Continuous Condition Monitoring," Energies, MDPI, vol. 12(19), pages 1-24, October.
  55. Chen, Jinglong & Pan, Jun & Zhang, Chunlin & Luo, Xiaoyu & Zhou, Zitong & Wang, Biao, 2017. "Specialization improved nonlocal means to detect periodic impulse feature for generator bearing fault identification," Renewable Energy, Elsevier, vol. 103(C), pages 448-467.
  56. Kong, Yun & Wang, Tianyang & Feng, Zhipeng & Chu, Fulei, 2020. "Discriminative dictionary learning based sparse representation classification for intelligent fault identification of planet bearings in wind turbine," Renewable Energy, Elsevier, vol. 152(C), pages 754-769.
  57. Seyed Abolfazl Mortazavizadeh & Reza Yazdanpanah & David Campos Gaona & Olimpo Anaya-Lara, 2023. "Fault Diagnosis and Condition Monitoring in Wave Energy Converters: A Review," Energies, MDPI, vol. 16(19), pages 1-16, September.
  58. Estefania Artigao & Sofia Koukoura & Andrés Honrubia-Escribano & James Carroll & Alasdair McDonald & Emilio Gómez-Lázaro, 2018. "Current Signature and Vibration Analyses to Diagnose an In-Service Wind Turbine Drive Train," Energies, MDPI, vol. 11(4), pages 1-18, April.
  59. 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.
  60. 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).
  61. Zengyi Zhang & Zhenru Shu, 2024. "Unmanned Aerial Vehicle (UAV)-Assisted Damage Detection of Wind Turbine Blades: A Review," Energies, MDPI, vol. 17(15), pages 1-31, July.
  62. Erguido, A. & Crespo Márquez, A. & Castellano, E. & Gómez Fernández, J.F., 2017. "A dynamic opportunistic maintenance model to maximize energy-based availability while reducing the life cycle cost of wind farms," Renewable Energy, Elsevier, vol. 114(PB), pages 843-856.
  63. Wenjie Wang & Yu Xue & Chengkuan He & Yongnian Zhao, 2022. "Review of the Typical Damage and Damage-Detection Methods of Large Wind Turbine Blades," Energies, MDPI, vol. 15(15), pages 1-31, August.
  64. Colak, Ilhami & Fulli, Gianluca & Bayhan, Sertac & Chondrogiannis, Stamatios & Demirbas, Sevki, 2015. "Critical aspects of wind energy systems in smart grid applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 155-171.
  65. Mohammed Dahane & M’hammed Sahnoun & Belgacem Bettayeb & David Baudry & Hamza Boudhar, 2017. "Impact of spare parts remanufacturing on the operation and maintenance performance of offshore wind turbines: a multi-agent approach," Journal of Intelligent Manufacturing, Springer, vol. 28(7), pages 1531-1549, October.
  66. Martinez-Luengo, Maria & Kolios, Athanasios & Wang, Lin, 2016. "Structural health monitoring of offshore wind turbines: A review through the Statistical Pattern Recognition Paradigm," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 91-105.
  67. Nayeripour, Majid & Mahdi Mansouri, M., 2015. "An advanced analytical calculation and modeling of the electrical and mechanical harmonics behavior of Doubly Fed Induction Generator in wind turbine," Renewable Energy, Elsevier, vol. 81(C), pages 275-285.
  68. Mahmood Shafiee & Fateme Dinmohammadi, 2014. "An FMEA-Based Risk Assessment Approach for Wind Turbine Systems: A Comparative Study of Onshore and Offshore," Energies, MDPI, vol. 7(2), pages 1-24, February.
  69. Jin, Xin & Ju, Wenbin & Zhang, Zhaolong & Guo, Lianxin & Yang, Xiangang, 2016. "System safety analysis of large wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 1293-1307.
  70. Pinar Pérez, Jesús María & García Márquez, Fausto Pedro & Tobias, Andrew & Papaelias, Mayorkinos, 2013. "Wind turbine reliability analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 463-472.
  71. Usama Aziz & Sylvie Charbonnier & Christophe Berenguer & Alexis Lebranchu & Frederic Prevost, 2022. "A Multi-Turbine Approach for Improving Performance of Wind Turbine Power-Based Fault Detection Methods," Energies, MDPI, vol. 15(8), pages 1-21, April.
  72. Giovanni Rinaldi & Philipp R. Thies & Lars Johanning, 2021. "Current Status and Future Trends in the Operation and Maintenance of Offshore Wind Turbines: A Review," Energies, MDPI, vol. 14(9), pages 1-28, April.
  73. Walsh, Jodi & Bashir, Imran & Garrett, Joanne K. & Thies, Philipp R. & Blondel, Philippe & Johanning, Lars, 2017. "Monitoring the condition of Marine Renewable Energy Devices through underwater Acoustic Emissions: Case study of a Wave Energy Converter in Falmouth Bay, UK," Renewable Energy, Elsevier, vol. 102(PA), pages 205-213.
  74. Faran Ahmed & Muhammad Naeem & Muhammad Iqbal, 2017. "ICT and renewable energy: a way forward to the next generation telecom base stations," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 64(1), pages 43-56, January.
  75. Li, Yanting & Liu, Shujun & Shu, Lianjie, 2019. "Wind turbine fault diagnosis based on Gaussian process classifiers applied to operational data," Renewable Energy, Elsevier, vol. 134(C), pages 357-366.
  76. 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.
  77. Ciulla, G. & D’Amico, A. & Di Dio, V. & Lo Brano, V., 2019. "Modelling and analysis of real-world wind turbine power curves: Assessing deviations from nominal curve by neural networks," Renewable Energy, Elsevier, vol. 140(C), pages 477-492.
  78. Kang, Jichuan & Sun, Liping & Guedes Soares, C., 2019. "Fault Tree Analysis of floating offshore wind turbines," Renewable Energy, Elsevier, vol. 133(C), pages 1455-1467.
  79. Chandrasekhar, Kartik & Stevanovic, Nevena & Cross, Elizabeth J. & Dervilis, Nikolaos & Worden, Keith, 2021. "Damage detection in operational wind turbine blades using a new approach based on machine learning," Renewable Energy, Elsevier, vol. 168(C), pages 1249-1264.
  80. Peng Guo & David Infield, 2012. "Wind Turbine Tower Vibration Modeling and Monitoring by the Nonlinear State Estimation Technique (NSET)," Energies, MDPI, vol. 5(12), pages 1-15, December.
  81. Kong, Yun & Qin, Zhaoye & Wang, Tianyang & Han, Qinkai & Chu, Fulei, 2021. "An enhanced sparse representation-based intelligent recognition method for planet bearing fault diagnosis in wind turbines," Renewable Energy, Elsevier, vol. 173(C), pages 987-1004.
  82. Artigao, Estefania & Martín-Martínez, Sergio & Honrubia-Escribano, Andrés & Gómez-Lázaro, Emilio, 2018. "Wind turbine reliability: A comprehensive review towards effective condition monitoring development," Applied Energy, Elsevier, vol. 228(C), pages 1569-1583.
  83. Kerman López de Calle & Susana Ferreiro & Constantino Roldán-Paraponiaris & Alain Ulazia, 2019. "A Context-Aware Oil Debris-Based Health Indicator for Wind Turbine Gearbox Condition Monitoring," Energies, MDPI, vol. 12(17), pages 1-19, September.
  84. Kong, Yun & Wang, Tianyang & Chu, Fulei, 2019. "Meshing frequency modulation assisted empirical wavelet transform for fault diagnosis of wind turbine planetary ring gear," Renewable Energy, Elsevier, vol. 132(C), pages 1373-1388.
  85. Abdul Ghani Olabi & Tabbi Wilberforce & Khaled Elsaid & Enas Taha Sayed & Tareq Salameh & Mohammad Ali Abdelkareem & Ahmad Baroutaji, 2021. "A Review on Failure Modes of Wind Turbine Components," Energies, MDPI, vol. 14(17), pages 1-44, August.
  86. 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.
  87. Alberto Pliego Marugán & Fausto Pedro García Márquez & Jesús María Pinar Pérez, 2016. "Optimal Maintenance Management of Offshore Wind Farms," Energies, MDPI, vol. 9(1), pages 1-20, January.
  88. Huang, Haoda & Liu, Qingsong & Yue, Minnan & Miao, Weipao & Wang, Peilin & Li, Chun, 2023. "Fully coupled aero-hydrodynamic analysis of a biomimetic fractal semi-submersible floating offshore wind turbine under wind-wave excitation conditions," Renewable Energy, Elsevier, vol. 203(C), pages 280-300.
  89. Seixas, M. & Melício, R. & Mendes, V.M.F., 2014. "Offshore wind turbine simulation: Multibody drive train. Back-to-back NPC (neutral point clamped) converters. Fractional-order control," Energy, Elsevier, vol. 69(C), pages 357-369.
  90. Magnus F. Asmussen & Jesper Liniger & Henrik C. Pedersen, 2021. "Fault Detection and Diagnosis Methods for Fluid Power Pitch System Components—A Review," Energies, MDPI, vol. 14(5), pages 1-15, February.
  91. Hines, Eric M. & Baxter, Christopher D.P. & Ciochetto, David & Song, Mingming & Sparrevik, Per & Meland, Henrik J. & Strout, James M. & Bradshaw, Aaron & Hu, Sau-Lon & Basurto, Jorge R. & Moaveni, Bab, 2023. "Structural instrumentation and monitoring of the Block Island Offshore Wind Farm," Renewable Energy, Elsevier, vol. 202(C), pages 1032-1045.
  92. Masoud Asgarpour & John Dalsgaard Sørensen, 2018. "Bayesian Based Diagnostic Model for Condition Based Maintenance of Offshore Wind Farms," Energies, MDPI, vol. 11(2), pages 1-17, January.
  93. Francisco Bilendo & Angela Meyer & Hamed Badihi & Ningyun Lu & Philippe Cambron & Bin Jiang, 2022. "Applications and Modeling Techniques of Wind Turbine Power Curve for Wind Farms—A Review," Energies, MDPI, vol. 16(1), pages 1-38, December.
  94. Cong Yang & Zheng Qian & Yan Pei & Lu Wei, 2018. "A Data-Driven Approach for Condition Monitoring of Wind Turbine Pitch Systems," Energies, MDPI, vol. 11(8), pages 1-17, August.
  95. Pierre Tchakoua & René Wamkeue & Mohand Ouhrouche & Fouad Slaoui-Hasnaoui & Tommy Andy Tameghe & Gabriel Ekemb, 2014. "Wind Turbine Condition Monitoring: State-of-the-Art Review, New Trends, and Future Challenges," Energies, MDPI, vol. 7(4), pages 1-36, April.
  96. Yang, Ruizhen & He, Yunze & Zhang, Hong, 2016. "Progress and trends in nondestructive testing and evaluation for wind turbine composite blade," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1225-1250.
  97. Yuri Merizalde & Luis Hernández-Callejo & Oscar Duque-Perez & Víctor Alonso-Gómez, 2019. "Maintenance Models Applied to Wind Turbines. A Comprehensive Overview," Energies, MDPI, vol. 12(2), pages 1-41, January.
  98. Miao, Yonghao & Zhao, Ming & Liang, Kaixuan & Lin, Jing, 2020. "Application of an improved MCKDA for fault detection of wind turbine gear based on encoder signal," Renewable Energy, Elsevier, vol. 151(C), pages 192-203.
  99. Wen, Songkang & Li, Yanting & Su, Yan, 2022. "A new hybrid model for power forecasting of a wind farm using spatial–temporal correlations," Renewable Energy, Elsevier, vol. 198(C), pages 155-168.
  100. Unai Elosegui & Igor Egana & Alain Ulazia & Gabriel Ibarra-Berastegi, 2018. "Pitch Angle Misalignment Correction Based on Benchmarking and Laser Scanner Measurement in Wind Farms," Energies, MDPI, vol. 11(12), pages 1-20, December.
  101. Yingying Zhao & Dongsheng Li & Ao Dong & Dahai Kang & Qin Lv & Li Shang, 2017. "Fault Prediction and Diagnosis of Wind Turbine Generators Using SCADA Data," Energies, MDPI, vol. 10(8), pages 1-17, August.
  102. Mérigaud, Alexis & Ringwood, John V., 2016. "Condition-based maintenance methods for marine renewable energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 53-78.
  103. Fallahi, F. & Bakir, I. & Yildirim, M. & Ye, Z., 2022. "A chance-constrained optimization framework for wind farms to manage fleet-level availability in condition based maintenance and operations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
  104. Rybak, Aurelia & Rybak, Aleksandra & Kolev, Spas D., 2024. "Development of wind energy and access to REE. The case of Poland," Resources Policy, Elsevier, vol. 90(C).
  105. Tziavos, Nikolaos I. & Hemida, H. & Dirar, S. & Papaelias, M. & Metje, N. & Baniotopoulos, C., 2020. "Structural health monitoring of grouted connections for offshore wind turbines by means of acoustic emission: An experimental study," Renewable Energy, Elsevier, vol. 147(P1), pages 130-140.
  106. Gonzalez, Elena & Stephen, Bruce & Infield, David & Melero, Julio J., 2019. "Using high-frequency SCADA data for wind turbine performance monitoring: A sensitivity study," Renewable Energy, Elsevier, vol. 131(C), pages 841-853.
  107. Chen, Jinglong & Pan, Jun & Li, Zipeng & Zi, Yanyang & Chen, Xuefeng, 2016. "Generator bearing fault diagnosis for wind turbine via empirical wavelet transform using measured vibration signals," Renewable Energy, Elsevier, vol. 89(C), pages 80-92.
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