A decision Tree Based Approach for Data Analysis and Fault Prediction For Wind Turbine Using SCADA dataset

  Roheela Amin,  Sushma Gupta,  Muheet Ahmed Butt,  Majid Zaman

The main objective of Supervisory Control and Data Acquisition (SCADA) is to give a means to the human operator to control and to command a highly automated process. Supervisory control and data acquisition systems (SCADA) are widely used in industries for supervisory control and data acquisition of industrial processes. It has also revolutionized the field of data sciences in a much inevitable manner. The communication between the control centre of SCADA and the remote station takes place by various communication channels such as optical fibre cables, microwave technology and power line carrier communication. The presence of such an efficient system give rise to certain faults results in malfunction of such systems. As the demand for wind energy continues to grow at exponential rate, reducing operation and maintenance costs and improving reliability have become top priorities in wind turbine maintenance strategies. Prediction of wind turbine fault before they reach a catastrophic stage is critical to reduce the operational and maintenance cost due to unnecessary scheduled maintenance. To this end, it is important to be able to perform maintenance before it’s needed. Instead, by performing complex analysis of existing data from turbine’s supervisory control and data acquisition system (SCADA) system, valuable insights into turbine performance can be obtained at a much lower cost. This paper proposes a methodology of fault prediction for wind turbine based on stored SCADA data set using decision tree approach. Fault analysis and diagnosis of faults help in protecting both hardware and software of devices employed in SCADA based systems. On the basis of information received, the SCADA operator is in a position to take important decision related to smooth and faultless generation, transmission and distribution of power. The proposed research provides insight analysis for relationship ships of various attributes like rotor speed, turbine speed, wind speed, power and output of the dataset and also provides fault analysis using Decision Tree Data Mining approach on the said dataset care of various parameters.

Keywords- SCADA System, Wind Turbine, Decision Tree Algorithm

Unique Identification Number - IJEDR1804091
Page Number(s) - 509-518
Pubished in - Volume 6 | Issue 4 | December 2018
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  Roheela Amin,  Sushma Gupta,  Muheet Ahmed Butt,  Majid Zaman,   "A decision Tree Based Approach for Data Analysis and Fault Prediction For Wind Turbine Using SCADA dataset", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.6, Issue 4, pp.509-518, December 2018, Available at :http://www.ijedr.org/papers/IJEDR1804091.pdf