光伏电站维修智能辅助机器人的研发

Research and Development of Intelligent Auxiliary Robots for Maintenance of Photovoltaic Power Plants

50MW以上中大型光伏电站多置于自然采光条件好的废弃矿坑、不适合农林耕作的连片丘陵荒地、戈壁滩、荒漠等地貌地区。对于目前尚不成熟的光电生产技术,硬件设备的维修维护工作是电站生产的重要组成部分,而地貌复杂性给维修维护工作增加了若干额外难度。文章对荒漠条件下的维修智能辅助机器人进行研发,通过跟随控制技术和UWB-AOA定位系统的应用,使其具有智能生产属性。这些技术的应用让维修智能辅助机器人具有了自动跟随、定位两大亮点。自动跟随的维修智能辅助机器人,不仅可以提供现场维修物料的搬运,也具备了运输工具箱检修维护时使用的安全升降梯、移动测试站等功能。在模拟地图下可以实时定位及实现现场监控能力,实时向指挥中心汇报现场工作情况,实现维修生产过程的智能监管。本研发设备的应用,将会促进推广新能源智慧场站建设的进程[5]。

Large and medium-sized photovoltaic power plants with a capacity of over 50MW are often located in abandoned mines with good natural lighting conditions,contiguous hilly wasteland that is not suitable for agricultural and forestry cultivation,Gobi Desert,and other landform areas.For the currently immature optoelectronic production technology,the maintenance and repair of hardware equipment is an important component of power plant production,and the complexity of the terrain adds several additional difficulties to the maintenance and repair work[2-4].The article focuses on the research and development of intelligent auxiliary robots for maintenance under desert conditions,utilizing tracking control technology and UWB-AOA positioning system to endow them with intelligent production attributes.The application of these technologies has provided intelligent maintenance assistance robots with two major highlights:automatic following and positioning.The automatic following intelligent repair assistance robot not only provides onsite transportation of repair materials,but also has functions such as safety elevators and mobile testing stations for transportation toolbox maintenance.Under the simulated map,real-time positioning and on-site monitoring capabilities can be achieved,and real-time reporting of on-site work conditions to the command center can be achieved,achieving intelligent supervision of the maintenance and production process.The application of this research and development equipment will promote the process of promoting the construction of new energy smart stations.