WANG Zhen, LI Guoqing, FU Wang'an, et al. Reliability modeling and analysis of wind turbine based on distribution function optimization[J]. Thermal power generation, 2024, 53(11): 56-65.
DOI:
WANG Zhen, LI Guoqing, FU Wang'an, et al. Reliability modeling and analysis of wind turbine based on distribution function optimization[J]. Thermal power generation, 2024, 53(11): 56-65. DOI: 10.19666/j.rlfd.202403082.
Reliability modeling and analysis of wind turbine based on distribution function optimization
Reliability model is the foundation of reliability analysis. Conventional reliability modeling takes the entire system as the research object
and uses all fault data to fit the distribution function of the system
estimate parameters
and optimize the model
thus to determine the distribution type and distribution function of the system
and then to calculate the reliability indicators of the system. Wind turbine is a typical complex electromechanical system
with different functions
structures
and fault forms of each subsystem. It is obviously inappropriate to use one distribution function to determine the fault distribution of the entire system. Therefore
based on the collected and sorted fault data of wind turbines
the distribution function optimization-based reliability modeling and analysis technology of wind turbines is proposed. By applying the commonly used exponential distribution
normal distribution
log-normal distribution
Weibull distribution and gamma distribution
the distribution function fitting
parameter estimation and goodness of fit analysis of the fault interval of each subsystem of wind turbines are carried out
and the distribution function and subsystem reliability function of the fault interval time of each subsystem are determined. On this basis
a Copula connection function is used to establish the reliability function model for wind turbines
taking into account the fault correlation between subsystems. Moreover
an example analysis is conducted on the fault data of an offshore wind turbine
which verifies the feasibility of the proposed method.