A new probabilistic model with simulation study: Its practical implementations using the energy consumption in urban planning

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.

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Publication Details

Journal
Alexandria Engineering Journal
Published
2024-11-20
DOI
https://doi.org/10.1016/j.aej.2024.11.027
Primary Topic
Transportation Planning and Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

A new probabilistic model with simulation study: Its practical implementations using the energy consumption in urban planning

Laila A. Al‐Essa, Hamiden Abd El‐Wahed Khalifa, S.J. Chen, Haifa Alqahtani et al.
Alexandria Engineering Journal
Transportation Planning and Optimization
article

A new probabilistic model with simulation study: Its practical implementations using the energy consumption in urban planning

Laila A. Al‐Essa, Hamiden Abd El‐Wahed Khalifa, S.J. Chen, Haifa Alqahtani, Tmader Alballa, Jiayi Zhang
article en

Abstract

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.

Alexandria Engineering JournalVol. 113
Princess Nourah bint Abdulrahman University (SA), Zhejiang A & F University (CN), Qassim University (SA), Al Ain University (AE), United Arab Emirates University (AE)
Princess Nourah Bint Abdulrahman University
Affordable and clean energy
Openalex Percentile: Top 82%
Transportation Planning and Optimization
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