Research On Intelligent Dispatch Mechanism Of Wind Power Operation And Maintenance Based On Cognitive Diagnosis

Traditional energy sources are drying up as industrial technologies continue to develop.Renewable energy represented by wind energy and photovoltaic is developing.Wind power generation is characterized by clean,renewable,environmentally friendly,short infrastructure cycle and flexible installation,and has become a typical representative of clean energy.Wind turbines are random and intermittent.The active power output of wind turbines varies randomly with wind speed.The active power flow of the wind power gathering system varies greatly,resulting in large reactive power loss and voltage change of the gathering system.At the same time,wind farms tend to be located in remote areas and in harsh environments,with most of the important components on top of towers,posing a huge maintenance challenge for operators.However,the traditional operation and maintenance training is to measure the ability of operation and maintenance personnel according to the examination,which is one-sided and cannot accurately measure the cognitive ability of operation and maintenance personnel.Moreover,the operation and maintenance tasks are conducted in groups,which are not targeted at specific wind power failures and are often inefficient.Thus raised the operation and maintenance cost,reduced the generation.Based on this,this article mainly work as follows:(1)according to the monitoring system of hunan electric wind energy co.,LTD.In this paper,a Physical system based on the information(Cyber-Physical-Systems,CPS)wind operational human-machine intelligent method,through the analysis of wind power failure monitoring CPS abnormal data,in the form of fault reasoning(EBR)to find fault,interturn short circuit fault,for example,by Maxwell fault modeling and fault analysis;(2)the knowledge base structure was introduced to connect nodes such as fault analysis and specific operation,and the cognitive measurement model was automatically generated through NEO4J;(3)study the determination of prior probability and conditional probability of cognitive measurement model,and conduct modeling and simulation of cognitive measurement model through Netica;(4)study the fuzzy rule "IF-THEN",build the operation and maintenance matching model,conduct simulation through MATLAB,and input the operation and maintenance personnel data for model analysis.Based on the above technologies,this paper studies the man-machine intelligence of wind power operation and maintenance through three steps.Firstly,fault diagnosis based on CPS can provide a basis for building cognitive measurement model.Then,the cognitive diagnosis model is constructed.The output result of the cognitive diagnosis model is the operational and maintenance personnel capability map,which serves as the input of the operational and maintenance matching model.Finally,the operation matching model is constructed.The three steps are interrelated to form a whole,which plays an important role in training operation and maintenance personnel,reducing failures of wind turbines,improving operation and maintenance efficiency and increasing power generation.The specific innovations of this paper are as follows :(1)the cognitive measurement model of wind power operation and maintenance based on bayesian network is proposed in the field of wind power,which breaks the form of cognitive measurement through examination in traditional wind power training;(2)design conditional probability according to the method of electrical analysis correlation degree to improve the accuracy of cognitive measurement model;(3)the wind power fault operation and maintenance matching model and scrambling operation and maintenance dispatching mechanism are proposed,which breaks the traditional grouping dispatching mechanism.