Research On Operational Maintenance Ship Path Scheduling Optimization Method Based On Chaotic Cloud Quantum Bat Algorithm For Offshore Wind Farm

China has developed rapidly in offshore wind power.In 2020,the installed capacity of offshore wind power will be the first in the world,and it has become the most important offshore wind power development market in the world.But offshore wind power development is still lagging behind onshore wind power.In addition to the difficulties in offshore wind power development,high construction cost and immature technology,the difficulty of operation and maintenance of offshore wind turbine units and high cost are also one of the main reasons for limiting the large-scale development of offshore wind power.Therefore,it is of great practical significance and application value to carry out the research on offshore wind power operation and maintenance methods.In this paper,the offshore wind farm is taken as the research object,aiming at the route scheduling planning of the operation and maintenance ship,the optimization model of the route scheduling of the offshore wind farm operation and maintenance ship satisfying the reliability and economic factors of the wind turbine is studied.The chaos cloud quantum bat algorithm is established(CCQBA)is used to optimize the route of the offshore wind farm operation and maintenance ship.The feasibility and superiority of the new method are evaluated by simulation with the measured wind field data.The main contents and achievements of this paper are as follows:(1)According to the characteristics of operational maintenance path scheduling task of offshore wind power,a set of task encoding and decoding method is established.The comprehensive efficiency of ship type,sea condition and fault level of wind turbine on operational maintenance path scheduling of offshore wind power is calculated.These above three factors were aggregated with corresponding path lengths into a path matrix to construct an objective function according to the task code decoding method,and an offshore wind power operational maintenance path scheduling model was established that satisfied reliability indexes,economic indexes as well as time indexes.(2)Considering the solution of operational maintenance path scheduling model of offshore wind power,the algorithm is prone to fall into local optimum,slow convergence rate and low population convergence rate at the later iteration stage of bat algorithm.By introducing the improved position update formula of quantum computation to increase the convergence efficiency of population,3D Cat mapping chaotic generator is used to carry out local chaotic disturbance to individuals whose fitness values are poor and iterate to a certain number of times in the bat algorithm,X condition cloud generator is used to speed up local search for the better fitness part of the bat algorithm,and mixed execution parameters(mix_exe)and interference scale factor(dis_Sca)to control the improved algorithm,put forward the Chaos Cloud Quantum Bat algorithm(CCQBA),test the performance of the algorithm,and give the recommended values of the relevant parameters.(3)Integrating the operational maintenance path scheduling model of offshore wind power and chaos cloud quantum bat algorithm,an intelligent operational maintenance path scheduling optimization process of offshore wind power based on CCQBA is established.According to the historical operation and maintenance data of offshore wind power,the simulation experiment of the model is completed,and the feasibility and superiority of the optimization method established in this paper are verified by comparing and analyzing with the traditional operational maintenance path scheduling method.