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Bivariate Copula Modeling of Electricity Load, Case Study of Kwame Nkrumah University of Science and Technology

机译:电力负荷的双变量Copula建模,Kwame Nkrumah科技大学的案例研究

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Dependence between random variables is a phenomenon that cannot be over emphasized. This study considered the dependence between consumption and maximum demand for a bulk electricity customer when it comes to its electricity load. The study applied the Clayton, Frank, Gumbel, Joe and Tawn Type 1 copulas to the realizations of the random variables (consumption and maximum demand). Considering the AICs and BICs of the models under study, the Tawn Type 1 copula model best represented the dependence between consumption and maximum demand. Using the inverse marginal distributions of both consumption and maximum demand, actual values were obtained from the pseudoobservations provided by the Tawn Type 1 copula. All the models revealed the presence of lower tail dependence between the two variables, with the exception of the Frank copula. The selected model was used to forecast load consumption and maximum demand.
机译:随机变量之间的依存关系是不能过分强调的现象。这项研究考虑了电力客户的电力消耗与最大需求之间的依赖关系。该研究将Clayton,Frank,Gumbel,Joe和Tawn 1类copulas用于实现随机变量(消费和最大需求)。考虑到所研究模型的AIC和BIC,Tawn Type 1 copula模型最能代表消费与最大需求之间的依赖关系。使用消耗量和最大需求量的逆边际分布,可以从Tawn Type 1 copula提供的伪观测中获得实际值。除了弗兰克·科普拉(Frank copula)之外,所有模型都揭示了两个变量之间存在较低的尾部依赖关系。所选模型用于预测负载消耗和最大需求。

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