Wind turbine generator short-term reliability prediction method considering operating state

Abstract

The invention relates to a wind turbine generator short-term reliability prediction method considering the operating state, which comprises the steps of acquiring state parameters of a wind turbine generator through a state monitoring and data acquisition system, classifying the state monitoring parameters into two categories; establishing a back-propagation neural network based state parameter prediction model in allusion to equipment temperature parameters, calculating the protective action probability based on prediction residual distribution characteristics, and calculating the protective action probability according to the out-of-limit time in allusion to other parameters; carrying out statistics on the outage times and the speed at an outage moment of the wind turbine generator according to wind power station operation and maintenance data and SCADA (Supervisory Control And Data Acquisition) data, and building a wind speed dependent wind turbine generator statistical outage model; and calculating the wind turbine generator short-term outage probability by combining outage statistical information and state parameter out-of-limit information. The method provided by the invention can accurately evaluate the outage risk of a wind turbine generator in a short term, the accuracy of a wind turbine generator short-term outage model is greatly improved, and technical reference is provided for short-term reliability evaluation and safe and economical operation of the whole wind power station.

Description

technical field [0001] The invention belongs to the technical field of safety evaluation of new energy electric equipment, and relates to a short-term reliability prediction method of wind turbines taking into account the operating state. Background technique [0002] Wind turbines are key equipment in wind farms, and their reliability is closely related to the safe and economical operation of wind farms. Due to long-term work in harsh natural environments, the outage rate of wind turbines is much higher than that of traditional power transmission and transformation equipment. Effectively predicting the reliability of wind turbines in a short period of time in the future is of great value to the output prediction and control of wind farms. [0003] Using statistical methods to obtain equipment reliability parameters is currently the main means of reliability assessment and prediction of wind turbines. Many foreign institutions have carried out statistics on the reliability...

AI Technical Summary

Problems solved by technology

However, this type of model is difficult to apply to the short-term reliability prediction of wind turbines. The main reasons include: 1) The reliability of some mechanical and electrical components not only depends on product quality and maintenance, but also has a close relationship with the natural environment and operating conditions , the existing statistical data do not take these factors into account; 2) Due to the real-time changes in the natural environment and operating conditions, static and constant reliability statistical indicators are difficult to reflect the current outage risk of wind turbines

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