摘要
风力发电检测面临着提供有效数据检测和处理的难题。借助无人机和边缘计算的优势,可大幅降低风电发电场检测成本。在保证数据准确性的前提下,为最小化无人机能耗,对无人机的轨迹和计算操作联合优化;为克服风对无人机轨迹规划的影响,对无人机飞行速度和卸载位置进行优化;其次,采用拉格朗日对偶法对卸载参数进行优化。仿真结果验证了该方法的有效性。
Wind turbine detection is facing the challenge of providing valid data sensing and transmission.With the respective advantages of unmanned aerial vehicle and edge computing,the detection cost of wind farm can be greatly reduced.The UAV energy consumption is minimized by jointly optimize the UAV trajectory and computation operations,while guaranteeing the data accuracy.To overcome the influence of wind on UAV trajectory planning,the UAV flight speed and offloading location is optimized.Then,the Lagrangian dual algorithm is adopted to optimize the offloading parameters.The simulation results verify the effectiveness of the proposed approach.
出处
《工业控制计算机》
2022年第5期53-54,57,共3页
Industrial Control Computer
关键词
风电机组
无人机
边缘计算
拉格朗日对偶法
wind turbine
unmanned aerial vehicle
edge computing
Lagrangian dual algorithm
