基于计算机视觉、低成本硬件和深度学习的太阳跟踪系统新方法
New approach for solar tracking systems based on computer vision, low cost hardware and deep learning
摘要：
在这项工作中，太阳跟踪系统的一种新方法。由于当前系统在成本和操作问题方面的限制，已经开发了一种基于低成本、计算机视觉开放硬件和深度学习的新方法。在Plataforma solar de Almeria（PSA）成功进行的初步测试显示了巨大的潜力，并显示新方法是传统系统的良好替代品。所提出的方法可以为太阳跟踪系统控制提供关键变量，如云运动预测，块和阴影检测，大气衰减或集中的太阳辐射的措施，这可以改善系统的控制策略，从而提高系统的性能。
英文摘要：
In this work, a new approach for Sun tracking systems is presented. Due to the current system limitations regarding costs and operational problems, a new approach based on low cost, computer vision open hardware and deep learning has been developed. The preliminary tests carried out successfully in Plataforma solar de Almeria (PSA), reveal the great potential and show the new approach as a good alternative to traditional systems. The proposed approach can provide key variables for the Sun tracking system control like cloud movements prediction, block and shadow detection, atmospheric attenuation or measures of concentrated solar radiation, which can improve the control strategies of the system and therefore the system performance.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
