通过评估光伏系统的功率分布来检测明显的非典型行为,提出了一种改进的临近预报方法

S. Killinger, Bjorn Muller, Y. Saint-Drenan, R. McKenna
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引用次数: 6

摘要

在过去的几年里,光伏电站的装机容量急剧增加。确定特定区域内光伏系统集成的实际功率的常用方法通常使用来自测量的参考电厂的数据。显然,功率估计的精度取决于具有代表性的参考植物,这些植物不受强烈的个体特征的影响。这项贡献的目标是通过将光伏系统的测量功率与基于附近气象站和晴朗天空辐照度的模拟进行比较,来检测这种明显的非典型行为。研究了2012年和48个光伏系统每天的偏差,表明了独立于气象条件的系统特征。此外,还提出了一种自动检测此类意外偏差的方法。这可以作为动态临近投射算法的基础,该算法根据参考单元的(时间)适用性选择参考单元。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards an improved nowcasting method by evaluating power profiles of PV systems to detect apparently atypical behavior
The installed capacity of PV plants has increased dramatically in the past years. A common approach to determine the actual power of an ensemble of PV systems within a specific region typically employs data from measured reference plants. Obviously the precision of the power estimation depends on having representative reference plants, which are not influenced by strong individual characteristics. The goal of this contribution is to detect such apparently atypical behavior of PV systems by comparing their measured power to simulations based on a nearby weather station and clear sky irradiance. Deviations are studied in the course of each day for the year 2012 and 48 PV systems, indicating systematic characteristics independent from meteorological conditions. Additionally, an approach is presented to detect such unexpected deviations automatically. This can be the basis for a dynamic nowcasting algorithm, which selects the reference units based on their (temporal) suitability.
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