Research On Maintenance Decision Of Offshore Wind Turbine Considering Environmental Factors

Wind power has attracted worldwide attention and become the most rapidly developing renewable energy.In addition,offshore wind power is closer to the load center,thus it has broad development prospects.In recent years,offshore wind power in China has developed rapidly,and the installed capacity has increased rapidly.However,the development and operation of offshore wind power still face many challenges,mainly reflected in: huge investment,poor operating environment,difficult maintenance and high maintenance cost.The existing wind power maintenance strategy can not make a targeted maintenance plan,which is easy to cause insufficient or excessive maintenance.This paper takes offshore wind turbine and its components as the research object,the influence of wind speed and other environmental factors are considered,the maintenance strategies such as condition-based maintenance,multi-stage preventive maintenance,dynamic opportunity maintenance and multi-objective maintenance are comprehensively applied,and multi-objective maintenance decision optimization is carried out with the availability and cost rate as the optimization objectives.The main contents of this paper are as follows(1)Multi-level opportunistic maintenance strategy optimization for the offshore wind turbines based on effective age group.Taking the minimum maintenance cost rate as the goal and the optimal number of age groups as the decision variable,a multi-level preventive opportunistic maintenance optimization model is established.By dividing the age groups of operating components,the multi-level preventive opportunistic maintenance model is established by integrating the maintenance methods of replacement,preventive replacement and multi-level preventive maintenance.The results show that compared with the traditional preventive maintenance,the proposed optimization model can significantly reduce the cost rate.(2)Dynamic opportunistic maintenance optimization of offshore wind turbine considering the influence of wind speed.An opportunistic maintenance strategy based on dynamic maintenance threshold is proposed.The dynamic maintenance threshold is based on the static threshold and changes with the wind speed.The Markov model is used to generate the wind speed time series.With the objective of minimizing the maintenance cost rate,the multi component opportunistic maintenance optimization model of wind turbine is established,and the simulated annealing algorithm is used to obtain the optimal static maintenance threshold.The results show that compared with equal cycle maintenance and static threshold opportunistic maintenance strategy,dynamic opportunistic maintenance strategy can better formulate maintenance strategy according to wind speed level,effectively reduce cost rate and improve availability.(3)The opportunistic maintenance strategy optimization of wind turbine based on artificial neural network.According to the condition monitoring information,the artificial neural network method is used to predict the service life percentage of components;combined with the state of wind turbine,the failure time distribution prediction is carried out,and the conditional failure probability is used to represent the deterioration state of wind turbine components,and the single objective maintenance mathematical model based on availability and cost rate is established respectively;the multi-objective maintenance mathematical model is established with the highest availability and the lowest cost rate.Moreover,the NSGA-II algorithm is used to solve the model,and the optimal opportunistic maintenance strategy is obtained.The results show that compared with equal period preventive maintenance and single condition threshold opportunistic maintenance,the opportunistic maintenance strategy proposed in this paper can effectively reduce the maintenance cost rate,and multi-objective maintenance can provide more maintenance schemes according to the constraints.The main work of this paper includes:(1)according to the condition monitoring information,using artificial neural network to make the condition-based maintenance plan;(2)considering the influence of wind speed,making the dynamic opportunistic maintenance strategy;(3)based on the effective age of components,taking the optimal age group number as the decision variable,establishing the multi-level preventive opportunistic maintenance optimization model.The relevant research content can enrich the maintenance decision-making model and method system,and provide a theoretical basis for the formulation of maintenance plan of offshore wind farm.