An Opportunistic Maintenance Strategy And Optimization Of Operation And Maintenance Routing For Offshore Wind Farms

Offshore wind power is becoming the main growth point of the global wind power industry in recent years.As a large-scale equipment for the development of offshore renewable energy,offshore wind turbines have brought high equipment failure risk and great maintenance difficulty due to its complex structure,harsh operating environment and low accessibility of repair and maintenance.As a result,the availability and reliability of offshore wind turbines equipped in the current offshore wind farms are low,the economy is insufficient,and the cost of offshore wind power operation and maintenance remains high.In view of this,it is of great significance to carry out the research on the optimization of offshore wind power operation and maintenance with wide applicability and high reliability.Supported by system reliability theory and reinforcement learning algorithm,this paper studies the formulation of opportunity maintenance strategy and optimization of operation and maintenance routing for offshore wind farms.Aiming at the difference and random uncertainty caused by multi-source failure data and complex marine environment,this paper uses the method named Fuzzy Fault Tree Analysis to study the reliability of offshore wind turbine.According to the functional characteristics of offshore wind turbine systems,the component units are divided,the fault trees are constructed respectively,and the fuzzy failure probability is calculated.In view of the one sidedness of the traditional probabilistic importance measure,the fuzzy critical importance is introduced to calculate and rank the components of an offshore wind turbine,and the components with high importance are selected as the research object of opportunistic maintenance strategy,and the maintenance priorities of these components are divided.In order to reduce the overall average unit time maintenance cost,the two parameter Weibull distribution is used as the failure model of the offshore wind turbine,and the offshore wind turbine opportunitistic maintenance model is constructed under certain idealized assumptions.The statistical data of offshore wind power failure and O&M are widely collected,and the constrained nonlinear integer programming algorithm Python program is compiled to solve the opportunistic maintenance model.The simulation analysis of opportunistic maintenance strategies of single wind turbine and wind farm is realized respectively,the opportunistic maintenance and preventive maintenance time of key maintenance units of wind turbine are optimized,and the corresponding opportunistic maintenance interval is obtained.For the path planning of the ship whose task is wind power O&M,this paper designs the reinforcement learning simulation environment according to the actual layout of offshore wind farm,and uses different timing difference update algorithms to solve the optimal path of offshore wind farm maintenance operation based on the formulated opportunistic maintenance strategy,By comparing and analyzing the performance measurement index of the algorithm,the optimal solution algorithm of the operation and maintenance path optimization model in current paper is determined.