A new probabilistic model with simulation study: Its practical implementations using the energy consumption in urban planning - Jiayi Zhang; Shensheng Chen; Tmader Alballa; Laila A. AL-Essa; Haifa Alqahtani; Hamiden Abd El-Wahed Khalifa (Alexandria Engineering Journal)
Methods based on probability make use of data sets to recognize patterns, evaluate potential outcomes, and predict various scenarios. These methods are often empirically utilized to analyze data sets, with a particular focus on data sets related to energy. The rapid urbanization in China has led to an increase in the share of residential energy consumption in the overall energy consumption. Given the importance of probability-based methods in the energy sector, this paper introduces the weighted very flexible Weibull (WVF-Weibull) distribution as a novel probability distribution. We provide the point estimators and simulation studies carried out under various parameter settings. Finally, the WVF-Weibull distribution is implemented to examine the energy consumption data collected from the urban regions of China. Through the examination of six statistical tools, it has been established that the WVF-Weibull distribution is the optimal model among various probability distributions for energy consumption data.