Research On Optimization And Application Of Operation And Maintenance Path For Offshore Wind Farms

In recent years,an increasing number of people pay more attention to energy.Offshore wind power is one of the most promising and available new energy sources.How to find the optimal operation and maintenance path and increase the power generation of wind turbines is the mainstream direction of current research.Path planning technology can effectively improve the navigation efficiency of ships in offshore wind farms and enhance the power generation capacity of wind turbines.For this reason,In this paper,the traditional ant colony algorithm has slow convergence speed,easy to fall into local optimum and optimization ability,and improves the defects of the ant colony algorithm in the path planning of offshore wind power operation and maintenance.The main work of this paper is as follows:(1)Although the ant colony algorithm can effectively help the operation and maintenance personnel of offshore wind farms to find a more suitable path,it also has some obvious shortcomings,such as relatively long search time and very easy to fall into local optimal problems;In addition,the algorithm also consumes a lot of time to find more efficient paths,only to get suboptimal results.In response to the above problems,this paper proposes a GA-PACO based offshore wind farm operation and maintenance model.Specifically,the introduction of heuristic factors can optimize the local optimal solution,making the ant colony algorithm clearer when searching for the target.On this basis,increasing the pheromone regulation factor can make invalid paths be excluded from search and high-quality paths can be selected;Moreover,add pheromone regulators,which can exclude invalid paths from search and select high-quality paths.In addition,by fusing genetic algorithms,the optimal solution can be searched for by selecting,crossing,and mutating to simulate the natural evolution process,reduce the similarity of paths constructed by ant colonies,reduce the probability of algorithm stagnation,improve convergence speed,and improve the time efficiency and solution accuracy of the algorithm.(2)We should consider multiple operation and maintenance ships in the route planning of offshore wind power operation and maintenance to further increase the power generation of wind turbines.therefore,we propose a multi-agent based offshore wind farm operation and maintenance model,on the basis of improving the ant colony algorithm and fusing the genetic algorithm,we use the K-means clustering algorithm to divide each wind turbine regional cluster that needs to be repaired into K groups.A set of K objects is selected randomly or according to certain criteria as the initial clustering center of the cluster,and an operation and maintenance ship is assigned as an agent for maintenance.The parallel operation of multiple O&M vessels can effectively improve the working efficiency of wind turbines and the maintenance efficiency of O&M bodies,and ultimately increase the actual power generation of wind turbines.This paper adopts Anylogic simulation software,offshore wind power operation and maintenance adopts a combination of centralized monitoring and operation and maintenance base,and we can set the model,number and scale of wind turbines.The simulation experiments conducted on a series of excellent data sets show that the algorithm proposed in this paper has achieved better performance in global search and path planning than the current traditional algorithms.