Study On Fault Analysis And Equipment Maintenance Strategy Of Wind Power System

The world energy crisis is deepening and the natural environment is gradually deteriorating,so social demand for clean energy is increasing day by day.As an inexhaustible and pollution-free new energy,wind power resource is gradually becoming an important role in the field of electric power.Based on this trend,the installed capacity and structure complexity of wind power system is also increasing.However,as a compound system dominated by electric and mechanical structures,the problems of wear,degradation and failure in wind power system are also urgently needed to be solved.At the same time,overmaintenance caused by excessive maintenance and management will also waste resource,or lead to safety problems,and wind power plants have a set of maintenance plan to meet the characteristics of wind power generation has become a necessary condition for its sustainable development.First,this paper analyzes the background and necessity of the research on the maintenance strategy of wind power system.The theoretical knowledge,control technology and other information involved in this research are introduced,including(1)dynamic maintenance,(2)Markov theory,(3)state maintenance theory,(4)group maintenance theory.It clarifies the research objective and significance of this paper and lays a foundation for the follow-up research.Second,this paper introduces the structure of wind power system as well as corresponding functions and their importances.The related achievements of reliability analysis and maintenance theory and discussion results are introduced.Maintenance models commonly used in academic research are listed and analyzed :(1)perfect maintenance model,(2)imperfect maintenance model,(3)minimal maintenance model.Failure rate function and reliability function model of wind power system with multiple subsystems are established by analyzing the historical failure data of each subsystem.The degradation curves of each subsystem are also obtained and discussed.Third,based on the scientific principles of Markov decision model,this paper summarizes the wide application of Markov decision model in the field of equipment maintenance and production scheduling.Firstly,its dynamic characteristics are analyzed.Secondly,the feasibility of adopting Markov decision model in the study of dynamic maintenance strategy is evaluated.Taking economic benefits as the goal,the stochastic fluctuation of subsystem state transition probabilities and the flexible adaptability of maintenance scheme selections during the maintenance process of wind power system are summarized comprehensively.Then the mathematical framework model of dynamic maintenance strategy is established.Fourth,SAPSO algorithm,a new optimization algorithm combining the characteristics of Simulated Annealing algorithm with Particle Swarm Optimization algorithm,is adopted in this paper,and applied to the dynamic maintenance strategy to verify.Taking nine subsystems of a wind power system as an example,the proposed method is used to optimize the dynamic maintenance strstegy.The experimental results show that compared with the current preventative maintenance strategy of wind farm,the dynamic maintenance strategy can create greater economic benefits and higher reliability,and the effect is good.Finally,based on the dynamic maintenance mathematical model mentioned above,this paper uses its results: dynamic maintenance time and maintenance action sequence to establish a set of group maintenance model based on a rolling time window to avoid over-maintenance phenomenon and consider the correlation.The model takes the economic relevance,structure relevance into account,and takes minimizing maintenance costs as the goal.In view of the frequent preventive maintenance problems,this paper has made corresponding adjustments,using MATLAB simulation software as the simulation platform to establish the model,and add the related parameters and model of each subsystem,the simulation results obtained large amount of cost savings and time savings,it provides references for wind power enterprises’ maintenance plans.