Fault prevention and diagnosis through scada temperature data analysis of an onshore wind farm

• Autorzy: Astolfi D. , Castellani F. , Terzi L.
• Języki publikacji: EN

Abstrakty

EN

Wind turbines, due to the distribution of the source, are an energy conversion system having low density on the territory, whose operational behaviour and production on the short term strongly depends on the stochastic nature of wind. They therefore need accurate assessment prior installation and careful condition monitoring in the operative phase. In the present work, smart post processing of Supervisory Control And Data Acquisition (SCADA) control system data sets is employed for fault prevention and diagnosis through the analysis of the temperatures of the machines. Automatic routines are developed for monitoring the evolution of all the temperature SCADA channels against power production. The methods are tested on an onshore wind farm sited in southern Italy, where nine turbines with 2 MW rated power are installed. The tests are performed both ex post and in real time: it is shown that in the former case, a major mechanical problem is detected, and in the latter case a significant problem to the cooling system is identified before compromising turbine functionality.

Słowa kluczowe

EN

wind energy; wind turbine; SCADA; control system; fault diagnosis

PL

energia wiatru; turbina wiatrowa; SCADA; system kontroli; diagnoza; błąd

• Wydawca: Polskie Towarzystwo Diagnostyki Technicznej
• Czasopismo: Diagnostyka
• Rocznik: 2014
• Tom: Vol. 15, No. 2
• Strony: 71--78
• Opis fizyczny: Bibliogr. 17 poz., rys., tab.

Twórcy

autor

Astolfi D.

• University of Perugia, Department of Engineering, Perugia, Italy

autor

Castellani F.

• University of Perugia, Department of Engineering, Perugia, Italy

autor

Terzi L.

• Sorgenia Green srl, Via Viviani 12, Milano, 20124, Italy

Bibliografia

• [1] Zaher A., McArthur S.D.J, Infield D.G., Patel Y.: Online wind turbine fault detection through automated SCADA data analysis. Wind Energy, Volume 12, Issue 6, 574-593 (2009).
• [2] Kusiak A., Li W.: The prediction and diagnosis of wind turbine faults. Renewable Energy 36 (2011) 16.
• [3] Bin Lu, Yaoyu Li, Xin Wu, Yang Z.: A review in recent advances in wind turbine condition monitoring and fault diagnosis. Power Electronics and Machines in Wind Applications, 2009. PEMWA 2009 IEEE, 1-7.
• [4] Kusiak A., Zhang Z., Verma A.: Prediction, operations and condition monitoring in wind energy. Energy 60 (0) (2013) 1-12.
• [5] Sainz E., Lllombart A., Guerrero J.J.: Robust filtering for the characterization of wind turbines: Improving its operation and maintenance. Energy Conversion and Management 50 (9) (2009) 2136-2147.
• [6] Schlechtingen M., Ferreira Santos I., Achiche S.: Wind turbine condition monitoring based on SCADA data using normal behavior models. Part 1: System description. Applied Soft Computing Volume 13 January 2013.
• [7] Elijorde F.I., Moon D., Ahn S., Kim S., Lee J.: Wind turbine performance monitoring based on hybrid clustering method. Future Information Communication Technology and Applications, Lecture Notes in Electrical Engineering Volume 235, 2013, pp 317-32.
• [8] Schlechtingen M., Ferreira Santos I., Achiche S.: Using Data-Mining Approaches for Wind Turbine Power Curve Monitoring: A Comparative Study. Sustainable Energy, February 2013, Volume PP, Issue 99, pp. 1-9, DOI:10.1109/TSTE.2013.2241797.
• [9] Yang W.,Court R., Jiang J.: Wind turbine condition monitoring by the approach of SCADA data analysis. Renewable Energy, May 2013, Volume 53, pp. 365-376, DOI:10.1016/j.renene.2012.11.030.
• [10] Castellani F., Garinei A., Terzi L., Astolfi D., Moretti M., Lombardi A.: A new data mining approach for power performance verification of an on-shore wind farm. Diagnostyka 14 (4) (2013) 35-42.
• [11] Castellani F., Garinei A., Terzi L., Astolfi D., Gaudiosi M.: Improving windfarm operation practice through numerical modelling and supervisory control and data acquisition data analysis. Renewable Power Generation, IET 8 (4) (2014) 367-379.
• [12] Castellani F., Astolfi D., Terzi L., Hansen K., Rodrigo Sanz J.: Analysing wind farm efficiency on complex terrains. J. Phys.: Conf. Ser. 524.
• [13] Barthelmie R., Hansen K., Pryor S.: Meteorological controls on wind turbine wakes. Proceeding of the IEEE 101 (4) (2013) 1010-1019.
• [14] Barthelmie R., Pryor S., Frandsen S., Hansen K., Schepers J., Rados K., Schlez W., Neubert A., Jensel L., Neckelmann S.: Quantifying the impact of wind turbine wakes on power output at offshore wind farms. Journal of Atmospheric and Oceanic Technology 27 (8) (2010) 1302-1317.
• [15] Mc Kay P., Carriveau R., Ting D.S.K.: Wake impacts on downstream wind turbine performance and yaw alignment. Wind Energy 16 (2013) 221-234.
• [16] Hansen K., Barthelmie R., Jensen J., Sommer A.: The impact of turbulence intensity and atmospheric stability on power deficits due to wind turbine wakes at Horns Rev offshore wind farm. Wind Energy 15 (1) (2012) 183-196.
• [17] Wilkinson M., Darnell B., Delft T.V., Harman K.: Comparison of methods for wind turbine condition monitoring with SCADA data. Renewable Power Generation, IET 8 (4) (2014) 390-397.