Improved Grey Verhulst model with the constant term and its application to forecast energy demand

IF 1.5 4区工程技术 Q3 ENGINEERING, CIVIL

Proceedings of the Institution of Civil Engineers-Engineering Sustainability Pub Date : 2022-02-04 DOI:10.1680/jensu.21.00085

Sevcan Demir Atalay, G. Calis, M. Adiyaman

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引用次数: 1

Abstract

The importance of accurate energy demand modeling has increased to support the decision-making of policy makers for ensuring a safe energy supply. However, forecasting energy demand has several difficulties due to the complexity in the supply line, demand increase, nonlinearity of data and volatility of energy usage. In this study, an improved Grey Verhulst model with the Constant Term (GVMCT), which is based on the Grey model, is introduced for improving the accuracy of energy demand prediction models. Within this context, total residential electricity demand of the U.S. and Turkey are modeled via linear and quadratic trend models as well as 3 grey models, including the proposed GVMCT model. The effectiveness of the models is assessed based on the Mean Absolute Error, Mean Squared Error, and Root-Mean Square Error. The results show that linear trend is the best performing model with a MAE of 34564.81844 for the U.S. data whereas the proposed GVMCT with a MAE of 4130.086917 outperforms all models for the data of Turkey.

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改进的常项灰色Verhulst模型及其在能源需求预测中的应用

准确的能源需求建模对于支持政策制定者确保安全能源供应的决策的重要性日益增加。然而，由于供给线的复杂性、需求的增加、数据的非线性和能源使用的波动性，能源需求预测存在一些困难。为了提高能源需求预测模型的准确性，本文在灰色模型的基础上，引入了一种改进的带有常数项的灰色Verhulst模型(GVMCT)。在此背景下，通过线性和二次趋势模型以及3个灰色模型对美国和土耳其的住宅总电力需求进行建模，其中包括提出的GVMCT模型。模型的有效性是基于平均绝对误差、均方误差和均方根误差来评估的。结果表明，对于美国数据，线性趋势是表现最好的模型，MAE为34564.81844，而对于土耳其数据，所提出的GVMCT模型的MAE为4130.086917，优于所有模型。

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来源期刊

Proceedings of the Institution of Civil Engineers-Engineering Sustainability ENGINEERING, CIVIL-ENGINEERING, CIVIL

CiteScore

3.70

自引率

16.70%

发文量

审稿时长

>12 weeks

期刊介绍： Engineering Sustainability provides a forum for sharing the latest thinking from research and practice, and increasingly is presenting the ''how to'' of engineering a resilient future. The journal features refereed papers and shorter articles relating to the pursuit and implementation of sustainability principles through engineering planning, design and application. The tensions between and integration of social, economic and environmental considerations within such schemes are of particular relevance. Methodologies for assessing sustainability, policy issues, education and corporate responsibility will also be included. The aims will be met primarily by providing papers and briefing notes (including case histories and best practice guidance) of use to decision-makers, practitioners, researchers and students.