Abstract: A method of controlling an operation of a floating wind turbine which performs a yaw rotation, a roll rotation and a pitch rotation, which controls a parameter of the operation of the wind turbine by determining a pitch rotation; determining a roll rotation; calculating a pitch difference between the determined pitch rotation and a wind turbine pitch reference; calculating a roll difference between the determined roll rotation and a wind turbine roll reference; determining a pitch and roll impact value based on the pitch difference and the roll difference; determining a reference of the parameter based on a predefined reference of the parameter and the pitch and roll impact value; and controlling the parameter of the wind turbine based on the reference of the parameter.

Abstract: Technical effects of the invention include use of a data-driven multivariate statistical method for the detection and isolation of sensor faults applied in a virtual flow metering context. In one implementation, the data-driven multivariate statistical method employs principal components analysis, weighted squared prediction error, and partial decomposition contribution plots.

Abstract: A method for controlling the rotor speed of a floating wind turbine including a floating foundation, a tower, a nacelle and a wind rotor having at least one wind blade includes the steps of: identifying a plurality of critical frequencies of the floating wind turbine, calculating a first plurality of critical rotor speeds of the wind rotor respectively corresponding to each critical frequency, calculating at least a second plurality of critical rotor speeds of the wind rotor by dividing each critical rotor speed of the first plurality of critical rotor speeds by a frequency coefficient, for each calculated critical rotor speed being lower than a maximum operational speed of the wind rotor defining a critical speed interval including the respective critical rotor speed, and operating the wind rotor at an operative rotor speed outside each defined critical speed interval.

Abstract: The present approach relates to establishing metrics for the computation of uncertainty boundaries for mean values for pressure and temperature drop error and mean values for mass flow error. Using such metric, sensor inaccuracies may be accounted for in the calibration and/or estimation processes of a virtual flow meter. For example, these values may be employed in the assessment of improvement in a calibration process of virtual flow meters, which will facilitate maintaining the accuracy of such virtual flow meters.

Abstract: Technical effects of the invention include use of a data-driven multivariate statistical method for the detection and isolation of sensor faults applied in a virtual flow metering context. In one implementation, the data-driven multivariate statistical method employs principal components analysis, weighted squared prediction error, and partial decomposition contribution plots.

Abstract: The present approach relates to establishing metrics for the computation of uncertainty boundaries for mean values for pressure and temperature drop error and mean values for mass flow error. Using such metric, sensor inaccuracies may be accounted for in the calibration and/or estimation processes of a virtual flow meter.