Impact of Sunshine Duration and Clearness Index on Diffuse Solar Radiation Estimation in Mountainous Climate

S. C. Nwokolo, Christiana Queennet Otse
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引用次数: 7

Abstract

In this paper, measured data of solar radiation was applied to develop forty-three (43) empirical models for estimation of monthly average diffuse solar radiation using clearness index, sunshine duration and a combination of them as predictors. The data covered a period of two years from May 2015 to April 2017 and was measured at Mehran University of Engineering and Technology, Hyderabad, Pakistan. Through a comprehensive statistical performance analysis, 43 dimensional models developed were tested for constructing the most accurate regression model to predict the monthly mean daily diffuse solar radiation in Hyderabad, Pakistan. On the whole, the model 42 – a hybrid of sunshine duration and clearness index predictors of diffuse fraction outperformed the remaining models proposed in this study. The best model (model 42) was then compared with 5 models and 5 measured data of diffuse solar radiation available in the literature and the NASA database by applying statistical indicators such as MBE, MPE, RMSE, RRMSE, R 2 and GPI. Through the analysis, the hybrid of sunshine duration and clearness index predictors of diffuse fraction model (model 42) was selected as the most appropriate model. The study concluded that the proposed hybrid model can serve as a baseline for the design of photovoltaic systems and estimate the monthly mean daily diffuse solar radiation on the horizontal surface for Hyderabad, Pakistan and other locations with similar local climate conditions. Citation:  Nwokolo, S.C. and Otse, C.Q. (2019). Impact of Sunshine Duration and Clearness Index on Diffuse Solar Radiation Estimation in Mountainous Climate. Trends in Renewable Energy, 5, 307-332. DOI: 10.17737/tre.2019.5.3.00107
日照时数和净度指数对山地气候散射太阳辐射估算的影响
本文利用太阳辐射的实测数据,建立了43个经验模型,以净度指数、日照时数及其组合为预测因子估算月平均太阳漫射辐射。该数据涵盖了2015年5月至2017年4月的两年时间,并在巴基斯坦海得拉巴的Mehran工程技术大学进行了测量。通过综合统计性能分析,对建立的43维模型进行了测试,以构建最准确的回归模型来预测巴基斯坦海得拉巴的月平均日漫射太阳辐射。总体而言,混合日照时数和弥散分数清晰度指数预测因子的模型42优于本研究提出的其他模型。利用MBE、MPE、RMSE、RRMSE、r2、GPI等统计指标,将最佳模型(模型42)与文献中已有的5个模型和5个太阳漫射辐射实测数据以及NASA数据库进行比较。通过分析,选择散射分数模型(模型42)的日照时数和清晰度指数混合预测因子作为最合适的模型。该研究的结论是,所提出的混合模型可以作为光伏系统设计的基线,并估计巴基斯坦海得拉巴和其他具有类似当地气候条件的地区水平面上的月平均日漫射太阳辐射。引用本文:Nwokolo, S.C.和Otse, C.Q.(2019)。日照时数和净度指数对山地气候散射太阳辐射估算的影响可再生能源动态,5,307-332。DOI: 10.17737 / tre.2019.5.3.00107
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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