A demand forecasting method for wind turbine spare parts based on fault tree analysis

Abstract

The invention discloses a method for predicting the demand for spare parts of wind power generating sets based on fault tree analysis. Firstly, an abstract model of the fault tree of wind power generating sets is established; The platform builds a fault tree simulation model and simplifies the Boolean function expression of the top event; finds the minimum cut set of the fault tree; writes the numerical operator function for calculating the probability importance and key importance index of each bottom event; the user inputs each The daily chemical annual failure probability of the bottom event, call the sub-function to output probability importance and key importance index; calculate the number of spare parts for each component in the future stage. The method of the present invention is based on the fault tree of the wind power generating set, and the model parameters are adjustable, adapting to the product differences of different manufacturers, adapting to different working conditions, refining the cause of the fault of the wind generating set, improving the use efficiency of spare parts, and reducing the inventory cost, so as to reduce the operating cost of wind power generation enterprises. target for maintenance costs.

Description

technical field [0001] The invention relates to the field of fault diagnosis of wind power generators, in particular to the problem of spare parts for wind power generators with variable speed and variable pitch. Background technique [0002] As a green, pollution-free and renewable new energy, wind energy is of great significance for solving environmental pollution and energy crisis. In recent years, wind power conversion technology has developed rapidly around the world, and the field of wind power generation has sprung up. By the end of 2016, the total installed capacity of wind turbines reached 486,749 megawatts, of which China accounted for 34.66%, ranking first in the world. [0003] As a new type of equipment in an emerging industry, wind turbines also show new characteristics in the demand for spare parts: there are many types of spare parts, large quantities of demand, poor versatility of spare parts, long procurement cycle, and loss of spare parts due to shortage ...

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the problem of inaccurate results of the existing demand forecasting and analysis methods for spare parts of wind power generating sets, the present invention provides a demand forecasting method for spare parts of wind power generating sets based on fault tree analysis

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