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Numerous practical applications within engineering disciplines, such as telecommunications, necessitate optimizing power delivery to a connected load. This pursuit, however, entails inherent internal losses, which can either equal or exceed the power supplied to the load. The Thevenin equivalent circuit is helpful in finding the maximum power a linear circuit can deliver to a load. It is assumed in this context that the load resistance can be adjusted.
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使用计算机视觉 (CVMPPT) 进行最大功率点跟踪的新算法.

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  • 1Laser and Plasma Research Institute, Shahid Beheshti University, Tehran, Iran.

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本研究介绍了一种用于太阳能模块最大功率点 (MPP) 追踪的新型计算机视觉算法. 它通过用数字图像处理取代代方法来提高速度和可靠性,改善太阳能收集.

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科学领域:

  • 可再生能源系统可再生能源系统
  • 光伏技术 光伏技术
  • 人工智能在能源中的作用

背景情况:

  • 太阳能模块的性能由功率-电压曲线定义,峰值跟踪对于最大功率提取至关重要.
  • 温度和辐射等环境因素会改变最大功率点 (MPP).
  • 部分遮阳会产生多个峰值,使传统的代最大功率点跟踪 (MPPT) 方法复杂化,这些方法在动态条件下通常是缓慢和不可靠的.

研究的目的:

  • 开发和验证一种基于计算机视觉的新算法,用于精确有效地跟踪太阳能模块的全球最大功率点 (MPP).
  • 克服传统代MPPT技术的局限性,特别是在部分遮阳和快速变化的环境条件下.

主要方法:

  • 开发了一种使用计算机视觉技术的新算法,用于识别太阳能模块功率-电压曲线上的全球MPP.
  • 该算法使用Matlab/Simulink实现,重点是用数字处理取代代模拟计算.
  • 进行了实验验证,以验证算法的有效性和实时性能.

主要成果:

  • 拟议的计算机视觉算法成功识别了全球最大功率点 (MPP),而不依赖于代电压计算.
  • 与传统方法相比,该算法在MPP跟踪中显示出更高的速度和更高的可靠性.
  • 实现了MPP的实时数据采集,证实了算法的实际适用性.

结论:

  • 新型计算机视觉算法为太阳能模块的最大功率点跟踪 (MPPT) 提供了显著的进步.
  • 这种方法提供了一种更快,更可靠和无代的方法来优化太阳能收集,特别是在具有挑战性的条件下.
  • 数字化,基于愿景的战略代表了未来太阳能能源管理系统的有希望的方向.