US 2022/0178353 A1Published application

A method for estimating remaining useful life of components of an operational wind turbine

AssigneesAcciona GeneracióN Renovable, S.A., Sentient Science Corporation

InventorsAdrijan RIBARIC, Juan GALLEGO-CALDERON, Mercedes IRUJO ESPINOSA DE MONTEROS

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Abstract

A method and a system for estimating remaining components life of an operational wind turbine from actual wind turbine operation conditions after it was commissioned, using a data acquisition module configured to measure real historical data of said operational wind turbine, and an additional state detection unit configured to identify historical states of operation. The method comprises extracting historical data from the data acquisition module at time intervals, identify operational states of the wind turbine, validate the identified operational states and identify uncertain data that do not match. Next, simulate a turbine model for each operational state identified and wind condition thereof at each time interval, and calculate a fatigue equivalent load for each operational state and wind condition.

Claims15

Dependent claims

A method for estimating remaining useful life of components of an operational wind turbine model executed by computational elements, wherein said computational elements are communicatively coupled to the operational wind turbine which comprises a data acquisition module configured to measure real historical data of said operational wind turbine and an additional state detection unit to identify historical states of operation, wherein said method comprises:

extracting historical data from the data acquisition module at a chosen time interval, said data comprising at least wind speed, blade pitch position and rotor speed;
identifying operational states of the wind turbine by means of the state detection unit for each chosen time interval, said operational states comprising at least Run, Idle, and Transition which in turn comprises:
Start up, Normal Stop, and Emergency Stop;
validating the identified operational states with the data extracted from the data acquisition module at each time interval, identifying and discarding uncertain data that do not match;
identifying a number of transitory events comprising the number of times the wind turbine has changed states,
identifying a prevailing operational state comprising the state at which the longest amount of time said wind turbine has spent over the chosen time interval thereof;
identifying wind condition, said wind condition comprising at least mean wind speed and turbulence intensity at the chosen time interval;
repeat previous steps for multiple time intervals,
wherein the method further comprises performing multiple simulations for the multiple time intervals chosen to estimate a fatigue equivalent load, said simulations consisting of obtaining the loads for the wind turbine model corresponding to wind condition for:
the prevailing operational state identified and duration thereof at each time interval, and
the transitory events identified at each time interval thereof.

8 more elements

A system for estimating remaining useful life of components of an operational wind turbine model, comprising at least said wind turbine model which comprises a data acquisition module configured to measure real historical data of said operational wind turbine, a state detection unit to identify historical states of operation, wherein said system comprises computational elements communicatively coupled thereof:

for extracting historical data from the data acquisition module at a chosen time interval, said data comprising at least wind speed, blade pitch position, and rotor speed;
for identifying operational states of the wind turbine by means of the state detection unit for each chosen time interval, said operational states comprising at least Run, Idle and Transition States which in turn comprises:
Start up, Normal Stop, and Emergency Stop;
for validating the identified operational states with the data extracted from the data acquisition module at each time interval, identifying and discarding uncertain data that do not match;
for identifying a number of transitory events comprising the number of times the wind turbine has changed states,
for identifying a prevailing operational state comprising the state at which the longest amount of time said wind turbine has spent over the chosen time interval;
for identifying wind condition, said wind condition comprising at least mean wind speed and turbulence intensity at the chosen time interval;
for repeating previous steps for multiple time intervals;
and
for performing multiple simulations for the multiple time intervals to estimate a fatigue equivalent load, said simulations consisting of obtaining the loads for the wind turbine model corresponding to wind condition for:
the prevailing operational state identified and duration thereof at each time interval, and
the transitory events identified at each time interval thereof.

9 more elements

Dependencies are inferred from the claim text.