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An ultra-short-term power prediction model based on machine vision for distributed photovoltaic system

机译:基于机器视觉的分布式光伏系统超短期功率预测模型

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Distributed photovoltaic(PV) system is easily affected by the cloud cluster moving in the sky because of its small scale. The instantaneous shelter caused by the moving cloud cluster may lead to the output power of photovoltaic system fluctuation violently. The cloud cluster monitoring device was designed, which aims to track the solar trajectory and take photos of the cloud cluster. The centroid position feature model and shape feature model were established based on image-based processing algorithms. They can forecast the position and shape of cloud cluster in the near future. And an ultra-short-term power prediction model based on machine vision for distributed photovoltaic system was established. Simulation results show that the established model can track the position of cloud cluster in the sky, and predict the shape-to-be of cloud cluster.
机译:分布式光伏(PV)系统由于规模小,很容易受到云团在天空中移动的影响。云团移动引起的瞬时遮挡可能导致光伏系统的输出功率剧烈波动。设计了云团监视设备,旨在跟踪太阳轨迹并拍摄云团的照片。基于图像处理算法建立了质心位置特征模型和形状特征模型。他们可以在不久的将来预测云集群的位置和形状。建立了基于机器视觉的分布式光伏系统超短期功率预测模型。仿真结果表明,所建立的模型能够跟踪云团在天空中的位置,并预测云团的未来形状。

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