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Daily clearness index profiles and weather conditions studies for photovoltaic systems

机译:每日清晰度指数简介和光伏系统的天气条件研究

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The increasing number of distributed photovoltaic (PV) systems connected to the power grid has made system planning and performance evaluation a challenging task. This is mainly due to the computational complexity, such as load flow analysis with large irradiance datasets collected from various locations of the installed PV farms. Solar irradiance data are known to possess the characteristic of high uncertainty, due to the random nature of cloud cover and atmospheric conditions. This paper presents the studies on the relationships of clustered clearness index profiles and the weather conditions obtained from the weather forecasting stations. Four years of solar irradiance and weather conditions data from two locations (Johannesburg and Kenya) were obtained and are used for the analysis. The preliminary study shows that the weather condition is related to the daily clearness index profiles. This work will form the basis for estimating the daily clearness index profile with weather conditions.
机译:连接到电网的分布式光伏(PV)系统的越来越多的系统规划和性能评估是一个具有挑战性的任务。这主要是由于计算复杂性,例如从安装的PV农场的各个位置收集的大型辐照度数据集的负载流量分析。由于云盖和大气条件的随机性,已知太阳辐照度数据具有高不确定性的特征。本文介绍了集群透明度指数曲线关系的研究和天气预报站获得的天气条件。获得了四年的太阳辐照度和天气条件来自两个地点(约翰内斯堡和肯尼亚)的数据,并用于分析。初步研究表明天气状况与日常透明度指数概况有关。这项工作将构成估计日常清除索引概况的基础,具有天气条件。

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