复杂天气和地形下的地表太阳辐射估算模型及其在超短期光伏发电功率预测中的应用

为了研究表面太阳辐射估算模型在超短期光伏功率预测中的应用,并减少多云天气对预测的干扰,利用电荷耦合器件/红外光谱(CCD/IRS)数据对表面太阳辐射估计模型进行了优化,构建了一种有效的超短期光伏功率预测模型,并通过实验证明了它的可靠性。首先介绍了CCD/IRS数据的原理,接着在考虑云量影响的情况下改进了太阳表面辐射估算模型。分别选择了多云和无云2种不同的天气类型来验证估算模型。实验结果表明:与传统算法相比,所提出的地表太阳辐射估算模型在多云天气和复杂地形条件下具有更大的优势,可用于光伏功率预测;基于地表太阳辐射估算模型构建的超短期光伏功率估算模型可用于在无云天气下获得准确有效的预测结果,提出的预测模型在多云天气中的偏差也得到了显着的改进。表面太阳辐射估算模型对于超短期光伏发电量的准确预测和安全运行具有重要的参考价值。

Surface Solar Radiation Estimation Model Under Mixed Weather and Terrain and Its Application in Ultra Short Term Photovoltaic Power Generation Prediction

In order to study the application of the surface solar radiation estimation model in ultra-short-term photovoltaic power prediction and reduce the interference of cloudy weather on the prediction, this paper optimized the surface solar radiation estimation model using charge coupled device/infrared radiation Spectroscopy (CCD/IRS) data, constructed an effective ultra-short-term photovoltaic power prediction model, and verified its reliability through experiments. Firstly, the principle of CCD/IRS data was introduced, then the surface solar radiation estimation model was improved considering the influence of cloud cover. Two different weather types, cloudy and cloudless, were selected to verify the estimation model. The experimental results showed that: Compared with traditional algorithms, the surface solar radiation estimation model proposed in this paper has greater advantages in cloudy weather and complex terrain conditions, and can be used for photovoltaic power prediction; The ultra-short-term photovoltaic power prediction model based on the surface solar radiation estimation model can obtain accurate and effective prediction results in cloudless weather, and the deviation of the proposed model in cloudy weather is also significantly improved. The surface solar radiation estimation model has important reference value for the accurate prediction and safe operation of ultra-short-term photovoltaic power generation.