A Bayesian network-based dynamic approximate weight wind turbine generator operation state comprehensive evaluation method

Abstract

According to the Bayesian network-based dynamic approximate weight wind turbine generator running state comprehensive evaluation method, The method comprises steps of utilizing scada data to determinea wind turbine generator state evaluation parameter vector, and classifying wind turbine generator fault modes; And constructing a three-layer Bayesian network to describe the operation parameter vector of the wind turbine generator and the fault causal relationship, determining the prior distribution of the Bayesian network parameter vector, and determining the hyper-parameter of the product Dirichlet distribution through the experience knowledge of the wind turbine generator. And determining the posterior probability distribution of the Bayesian network parameters. And calculating conditional probability distribution of each node in the Bayesian network under different states of father nodes of the node. And comprehensively evaluating the operation state of the wind turbine generator according to the dynamic approximate weight of the comprehensive evaluation of the operation state of the wind turbine generator. According to the method, the operation state of the wind turbine generator is evaluated rapidly and effectively, the abnormity and degradation trend of equipment are found in advance, predictive maintenance is achieved, faults are effectively avoided, economic losses arereduced, and the economy and safety of the wind power plant are improved.

Description

technical field [0001] The invention relates to a method for evaluating the state of a wind turbine, in particular to a method for comprehensively evaluating the operating state of a wind turbine based on a Bayesian network. Background technique [0002] As a clean, environmentally friendly and most exploitable new energy generation method, wind power generation is of great significance for improving the ecological environment and alleviating the tight power supply situation. With the rapid development of wind power generation, problems such as high management and maintenance costs and status assessment of wind turbines have become increasingly prominent. According to statistics, the operation and maintenance costs of onshore wind turbines account for about 10%-15%. Due to its more special operating environment, offshore wind farms have more stringent technical requirements, and the maintenance cost is as high as 20%-25%. The reason for the high unit maintenance cost is th...

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Problems solved by technology

One is to mine normal data information from scada historical data and establish a judgment model for wind turbine abnormality. This idea lacks research on the overall operating status of the wind turbine, resulting in a large judgment error

The above methods also have the disadvantages of large amount of calculation and harsh model operating environment.

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