The invention provides a complete
machine load
estimation control method for a wind
turbine generator. The method comprises the steps that S1,
original data are collected and preprocessed; s2, establishing a
load model of the wind generating set based on stress analysis; s3, establishing a load prediction model of the wind generating set based on the variable-
pitch motor data; s4, constructing a neural network prediction model; s5, using a
genetic algorithm to optimize the weight and the threshold of the neural network for training; and S6, adjusting. Through one-time sensor investment and calculation of a large amount of calculation and training work in the early stage, an actual model for reversely deducing a fan load from parameters of a variable-
pitch motor and a generator is obtained and is transmitted to a main controller, so that convenient load reduction control can be realized, subsequent repeated investment can be omitted at a wind
turbine generator, a large amount of hardware investment is saved, and the cost is reduced. Adjustment is carried out through
continuous monitoring and continuous
verification modeling in the later period, and rapid load
estimation and control of the whole life cycle of the wind
turbine generator can be achieved.