摘 要:在风力发电系统中,作为与外界环境直接接触的组成部分,叶片是风力发电机运行过程中主要能量捕获媒介,其性能的好坏将直接或间接影响整个系统的运行稳定性。因此,定期通过无人机对风力发电机进行内外缺陷检测,维护风电叶片具有必要性。为使风电场系统的停运检修时间尽可能缩短,减少因为弃风所带来的经济损失。基于模拟退火和改进遗传算法,对多无人机场景下风电系统的最优检测路线进行了研究。
关键词:模拟退火;遗传算法;最优规划
DOI:10.19850/j.cnki.2096-4706.2022.09.001
中图分类号:TP18 文献标识码:A 文章编号:2096-4706(2022)09-0001-06
Dynamic Path Optimal Planning Model for UAV Wind Power Inspection Based on Simulated Annealing and Improved Genetic Algorithm
LIN Yangzhi, DONG Jiaqi, QIN Lichaozheng
(Changsha University of Science and Technology, Changsha 410114, China)
Abstract: In the wind power generation system, the blade, as a part of the direct contact with the external environment, is the main energy capture medium during the operation process of the wind driven generator. Its good or bad performance will directly or indirectly affect the operation stability of the whole system. Therefore, it is necessary to regularly detect internal and external defects of wind driven generator by UAV and maintain wind turbine blades. In order to shorten the outage maintenance time of wind farm system as much as possible, reduce the economic loss caused by wind abandoning, based on simulated annealing and improved Genetic Algorithm, the optimal detection path of wind power system in multi-UAV scenario is studied.
Keywords: simulated annealing; Genetic Algorithm; optimal planning
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作者简介:林阳芷(2001—),女,汉族,浙江温州人,本科在读,研究方向:电力系统及其自动化;董佳琦(2000—),女,汉族,辽宁锦州人,本科在读,研究方向:电子与信息工程;秦李朝政(2003—),男,汉族,江苏徐州人,本科在读,研究方向:电力系统及其自动化。