Method for predicting the accumulation of ice on a rotor blade of a wind turbine and the use thereof

1. A method for predicting the accumulation of ice on a rotor blade of a wind turbine, comprising:

defining at least one of an upper threshold value or a lower threshold value for a system variable, which is associated with at least one of the mass of the rotor blade, or the mass of an ice attachment of the rotor blade;

acquiring system variable data during an acquisition time period for obtaining a curve profile of the system variable during the acquisition time period;

carrying out a compensation calculation of the curve profile for a prediction time period from the system variable data which were acquired during a partial time period of the acquisition time period in order to obtain a prediction curve;

carrying out at least one further compensation calculation of the curve profile for a further prediction time period from the system variable data which were acquired during another partial time period of the acquisition time period in order to obtain a further prediction curve;

determining at least one of whether or not the upper threshold value will be exceeded by one or more of the prediction curves in the future, or whether or not the lower threshold value will be undershot by one or more of the prediction curves in the future; and

outputting the result of the determination.

2. The method according to claim 1 , further comprising at least one of:

if it is determined that the upper threshold value will be exceeded by one or more of the prediction curves in the future, an ice warning message is output; or

if it is determined that the lower threshold value will be undershot by one or more of the prediction curves in the future, a free-of-ice message is output.

3. The method according to claim 1 ,

wherein

the system variable is proportional to at least one of the total mass of the rotor blade, or an additional deposit on the mass of the rotor blade.

4. The method according to claim 1 ,

further comprising:

determining and outputting at least one of

a prospective exceeding point of time when a minimum amount of ice on the rotor blade will be exceeded, or

a prospective undershooting point of time when a maximum amount of ice on the rotor blade will be undershot.

5. The method according to claim 1 ,

wherein the acquiring of system variable data comprises:

measuring a measurand in the temporal course of the acquisition time period; and

deducing the system variable from the measurement data.

6. The method according to claim 5 ,

wherein the measuring the measurand is measuring vibrations at or in the rotor blade.

7. The method according to claim 6 ,

wherein the deducing the system variable is deducing the system variable by a natural frequency analysis.

8. The method according to claim 1 ,

wherein each of the compensation calculations is respectively carried out for a prediction time period in the future, which is at maximum as long as the partial time period of acquired system variable data used for the respective compensation calculation.

9. The method according to claim 8 ,

wherein the prediction time period is of the same length as the partial time period of the acquired system variable data.

10. The method according to claim 1 ,

further comprising at least one of:

deducing a probability, whether or not a minimum amount of ice will be accumulated on a rotor blade, from at least one of the respective prediction time period, the respective exceeding point of time, or the respective curve profile of the respective prediction curve; or

deducing a probability, whether or not a maximum amount of accumulated ice on a rotor blade will be undershot, from at least one of the respective prediction time period, the respective undershooting point of time, or the respective curve profile of the respective prediction curve.

11. The method according to claim 1 , further comprising:

deducing the amount of ice which is expected to be accumulated on the rotor blade, from at least one of the respective prediction time period, the respective exceeding point of time, or the respective curve profile of the respective prediction curve.

12. The method according to claim 1 ,

wherein at least one of the compensation calculations is a linear or a square regression.

13. The method according to claim 12 ,

wherein all of the compensation calculations are a linear or a square regression.

14. The method according to claim 1 ,

wherein the partial time periods has a length of approximately one hour or more and the respective partial time periods thereof have a length of about 1 hour, about 2 hours or about 4 hours.

15. The method according to claim 14 ,

wherein at least three compensation calculations are carried out.

16. The method according to claim 1 ,

wherein the lengths of the respective partial time periods are defined in advance.

17. The method according to claim 16 ,

wherein the lengths of the respective partial time periods are defined in advance as at least one of a function of the location of the wind turbine, or a function of meteorological supporting data.

18. The method according to claim 1 ,

wherein the lengths of the respective partial time periods are adjusted during the operation of the wind turbine as a function of the plant size of the wind turbine.

19. The method according to claim 1 ,

wherein the lengths of the respective partial time periods are adjusted during the operation of the wind turbine as at least one of a function of the rotor blade speed of the rotor of the wind turbine, or a function of meteorological supporting data.