Implementation of Preventive and Corrective measures in SCADA based Wind Turbines

Wind energy is becoming increasingly important in addressing energy demand and environmental sustainability. It is driven by the outstanding offshore wind resource and the need to minimize carbon emissions from energy generation. A growing interest in wind turbine condition monitoring, which allows condition based rather than reactive or scheduled maintenance, stems from the difficulty of accessing and maintaining wind turbines offshore. Vibration analysis and oil debris detection are currently used wind turbine condition monitoring methods. The extra expenditures might be enormous when considering the number of turbines normally put in offshore wind farms, and specialist interpretation is usually required. However, extending SCADA data-based analysis could bring significant value to condition monitoring at little or no expense to the wind farm operator. This Research Paper focuses on wind turbine condition monitoring using only SCADA data. An early detection of operational defects or breakdowns allows for regular maintenance or repair, decreasing downtime and potentially preventing further damage. Comparing incoming operational SCADA data with results for relevant variables, like component temperature, produced from applicable models trained on SCADA data from a healthy wind turbine, yields useful component condition indicators. Anomalies in the variables of interest in the SCADA data indicate impending breakdowns. This method is used to derive machine-to-machine comparison of component condition Compared to developing separate turbine models, this saves significant computing work and model complexity. A real-time wind turbine power curve is also created using SCADA data and compared to a reference power curve to quickly discover abnormal behavior based on slight variations in the power curve.