模拟污染率:对气象参数的依赖

F. Wolfertstetter, S. Wilbert, Felix Terhag, N. Hanrieder, A. Fernández-García, C. Sansom, P. King, L. Zarzalejo, A. Ghennioui
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引用次数: 11

摘要

聚光太阳能(CSP)电站通常位于多尘环境中。污染在很大程度上取决于地点、时间、天气条件和镜面方向,其特征是污染率:每隔一段时间由于污染而造成的镜面反射的损失。在阿拉伯半岛等含尘量较大的地区,平均污染率可达2%/天。在某些日子(例如沙尘暴期间),污染率可能明显高于这一水平。污染率的测量活动是CSP工厂选址和工厂设计的兴趣所在,但它们既耗时又昂贵。在这项研究中,提出了一个基于物理方程的污垢模型,该模型描述了颗粒沉积过程,从中可以推导出污垢速率。该模式使用易于测量的气象参数作为输入参数,如气溶胶粒子数浓度、10米高度的风速和风向、相对湿度、温度和降水。利用摩洛哥和西班牙两个站点的测量数据对该模型进行了优化和验证。测量数据分为两部分。一种是通过参数化方法寻找最优模型参数。第二个数据集用于验证模型。模型偏差为0.1%/d,均方根偏差为0.4% /d。识别弱污染天数(<1%/d)的准确率超过90%,在85%的情况下正确回答了污染率是否高于1%/d的问题。聚光太阳能(CSP)电站通常位于多尘环境中。污染在很大程度上取决于地点、时间、天气条件和镜面方向,其特征是污染率:每隔一段时间由于污染而造成的镜面反射的损失。在阿拉伯半岛等含尘量较大的地区,平均污染率可达2%/天。在某些日子(例如沙尘暴期间),污染率可能明显高于这一水平。污染率的测量活动是CSP工厂选址和工厂设计的兴趣所在,但它们既耗时又昂贵。在这项研究中,提出了一个基于物理方程的污垢模型,该模型描述了颗粒沉积过程,从中可以推导出污垢速率。该模式使用易于测量的气象参数作为输入参数,如气溶胶粒子数浓度、10米高度的风速和风向、相对湿度、温度和降水。Th……
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modelling the soiling rate: Dependencies on meteorological parameters
Concentrating solar power (CSP) plants are often located in dusty environments. Soiling depends strongly on location, time, weather conditions and mirror orientation and is characterized by the soiling rate: the loss of the specular reflectance due to soiling per time interval. The average soiling rate can reach 2%/day on sites with heavy dust loads such as the Arabian Peninsula. On some days (for example during a sandstorm) the soiling rate can be significantly higher than that. Measurement campaigns for the soiling rate are of interest for the CSP plant site selection and the plant design, but they are time consuming and costly. In this study, a soiling model is presented that describes particle deposition processes based on physical equations from where the soiling rate can be derived. The model uses easily measureable meteorological parameters such as aerosol particle number concentration, wind speed and direction at 10 m height, relative humidity, temperature and precipitation as input parameters. The model has been optimized and validated using measurement data from two sites in Morocco and Spain. The measurement data have been divided into two parts. One was used to find optimum model parameters by parameterization. The second dataset was used to validate the model. The model reaches a bias of 0.1%/d and a root mean square deviation of 0.4 %/d. Days with weak soiling (<1%/d) rates are identified with an accuracy of more than 90 %, the question whether or not the soiling rate is above 1%/d is answered correctly in 85 % of the cases.Concentrating solar power (CSP) plants are often located in dusty environments. Soiling depends strongly on location, time, weather conditions and mirror orientation and is characterized by the soiling rate: the loss of the specular reflectance due to soiling per time interval. The average soiling rate can reach 2%/day on sites with heavy dust loads such as the Arabian Peninsula. On some days (for example during a sandstorm) the soiling rate can be significantly higher than that. Measurement campaigns for the soiling rate are of interest for the CSP plant site selection and the plant design, but they are time consuming and costly. In this study, a soiling model is presented that describes particle deposition processes based on physical equations from where the soiling rate can be derived. The model uses easily measureable meteorological parameters such as aerosol particle number concentration, wind speed and direction at 10 m height, relative humidity, temperature and precipitation as input parameters. Th...
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