The total solar radiation received by a specific region in a day is a significant weather-related parameter for most areas of application. Obtaining correct information from irradiation models reduces uncertainty in solar resource estimations, leading to improvements in solar energy production. This study introduces a copula method to correlate the sky clearness index and solar radiation at two meteorology stations in Peninsular Malaysia. Six types of marginal likelihood distribution namely; gamma, logistic, Weibull, Burr, lognormal, and normal were fitted to the data of solar radiation and sky clearness index. Using information from the best-fit marginal distributions, six copula function types were then applied to evaluate the dependence between the sky clearness index and solar radiation. The copula functions used were the Gumbel, Joe, Frank, Clayton, Gaussian, and Student’s t copulas. The Gaussian copula most accurately represented the dependence between the sky clearness index and solar radiation as measured by Akaike's Information Criteria (AIC) for testing goodness of fit. These probabilistic properties can provide useful information for solar energy planning and management.

对于大多数应用领域来说，一天中特定区域接收到的总太阳辐射是与天气相关的重要参数。从辐照模型中获取正确信息可减少太阳能资源估算的不确定性，从而提高太阳能生产。本研究介绍了一种 copula 方法来关联马来西亚半岛两个气象站的天空晴朗指数和太阳辐射。六种边际似然分布即；伽马、logistic、Weibull、Burr、对数正态和正态拟合太阳辐射和天空晴朗指数数据。使用来自最佳拟合边缘分布的信息，然后应用六种 copula 函数类型来评估天空晴朗指数和太阳辐射之间的依赖性。使用的 copula 函数是 Gumbel、Joe、Frank、t copulas。高斯 copula 最准确地代表了天空清晰度指数和太阳辐射之间的依赖关系，这是由 Akaike 的信息标准 (AIC) 测量的，用于测试拟合优度。这些概率特性可以为太阳能规划和管理提供有用的信息。