论文标题

卫星衍生的太阳辐射,用于日期和日内应用:季节和海拔的偏见和不确定性

Satellite-derived solar radiation for intra-hour and intra-day applications: Biases and uncertainties by season and altitude

论文作者

Carpentieri, Alberto, Folini, Doris, Wild, Martin, Vuilleumier, Laurent, Meyer, Angela

论文摘要

表面太阳辐射(SSR)的准确估计是对太阳资源和光伏发电的日期预测的先决条件。日内SSR预测是电力交易者以及太阳能电厂和电力电网的运营商所感兴趣的,他们试图通过匹配电源和需求来优化其收入并保持电网稳定性。我们的研究分析了系统的偏见和SSR估计值的不确定性,该估计值是在sarah-2和Heliomont算法下以时间内和日内时间尺度下的Sarah-2和Heliomont算法得出的。卫星SSR估计是根据2018年从200 m到3570 m的136个地面站进行了分析的。我们在瞬时,每小时和每日均值SSR中发现了主要的偏见和不确定性。在白天高峰期,瞬时卫星SSR分别以Sarah-2和Heliomont的平均绝对偏差(MAD)为110.4和99.6 W/M2,从而偏离了地面测量的SSR。对于白天的SSR,瞬时,每小时和每日均值的疯狂分别为91.7、81.1、50.8和82.5、66.7、42.9 w/m2,分别为Sarah-2和Heliomont。此外,Sarah-2瞬时SSR大大低估了半年冬季高于1000 m的太阳资源。与偏见的季节性相符的可能解释是,雪覆盖可能会被误解为高度较高的云。

Accurate estimates of the surface solar radiation (SSR) are a prerequisite for intra-day forecasts of solar resources and photovoltaic power generation. Intra-day SSR forecasts are of interest to power traders and to operators of solar plants and power grids who seek to optimize their revenues and maintain the grid stability by matching power supply and demand. Our study analyzes systematic biases and the uncertainty of SSR estimates derived from Meteosat with the SARAH-2 and HelioMont algorithms at intra-hour and intra-day time scales. The satellite SSR estimates are analyzed based on 136 ground stations across altitudes from 200 m to 3570 m Switzerland in 2018. We find major biases and uncertainties in the instantaneous, hourly and daily-mean SSR. In peak daytime periods, the instantaneous satellite SSR deviates from the ground-measured SSR by a mean absolute deviation (MAD) of 110.4 and 99.6 W/m2 for SARAH-2 and HelioMont, respectively. For the daytime SSR, the instantaneous, hourly and daily-mean MADs amount to 91.7, 81.1, 50.8 and 82.5, 66.7, 42.9 W/m2 for SARAH-2 and HelioMont, respectively. Further, the SARAH-2 instantaneous SSR drastically underestimates the solar resources at altitudes above 1000 m in the winter half year. A possible explanation in line with the seasonality of the bias is that snow cover may be misinterpreted as clouds at higher altitudes.

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