Prediction of natural gas demand by considering implications of energy-related policies: The case of Türkiye

IF 3.1 4区 工程技术 Q3 ENERGY & FUELS Energy Sources Part B-Economics Planning and Policy Pub Date : 2023-11-14 DOI:10.1080/15567249.2023.2274865
Huseyin Avni ES, Pınar Baban, Coskun Hamzacebi
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Abstract

ABSTRACTThe most important key to determining sustainable energy policies is reliable and accurate energy demand forecasting. Grey prediction, one of the demand forecasting methods, makes successful forecasts with limited data and without the need for any prior knowledge. In this study, GM (1,1) and Grey Verhulst from time series models and GM (1, N) model based on cause–effect relationship were used to forecast Türkiye’s natural gas demand. Dynamic grey forecasting models have been developed in order to obtain robust and reliable predictions. All developed models were evaluated according to performance criteria, and the superior model was obtained to be GM (1,5). Within the scope of the study, it was determined that models based on cause–effect relationship should be preferred instead of time series models. For this, population, the amount of electricity generated from natural gas, industrial production index, and building area are determined as independent variables. Three different scenarios were created taking into account the specified independent variables, and natural gas demand until 2025 was obtained. According to the forecasting results, Türkiye’s natural gas demand for 2025 will happen as an interval between 29.61 and 53.62 mtoe based on the low and high scenarios, respectively. According to the expected scenario, this demand would be realized around 40 mtoe for Türkiye in the year 2025. Finally, Grey Dynamic Decision Support System was designed and introduced to easily apply the dynamic grey models by end-users.KEYWORDS: Energy policiesforecastingGrey Dynamic decision support systemGrey prediction modelsNatural gas Disclosure statementNo potential conflict of interest was reported by the author(s).Ethical approvalThis article does not include any studies with human participants or animals performed by any of the authors.
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考虑能源相关政策影响的天然气需求预测:以 rkiye为例
摘要可靠、准确的能源需求预测是制定可持续能源政策的关键。灰色预测是需求预测的一种方法,它在数据有限的情况下,不需要任何先验知识,就能成功地进行预测。本研究采用时间序列模型GM(1,1)和Grey Verhulst模型以及基于因果关系的GM (1, N)模型对 rkiye天然气需求进行预测。为了获得稳健可靠的预测结果,建立了动态灰色预测模型。根据性能标准对所开发的模型进行评价,优选GM模型(1,5)。在研究范围内,确定了基于因果关系的模型,而不是时间序列模型。为此,确定人口、天然气发电量、工业生产指数、建筑面积为自变量。考虑到指定的自变量,创建了三种不同的情景,并获得了到2025年的天然气需求。根据预测结果,根据低情景和高情景,2025年 rkiye的天然气需求将分别发生在29.61至53.62百万吨油当量之间。根据预期的情景,到2025年,这种需求将在4000万吨左右实现。最后,设计并引入灰色动态决策支持系统,方便终端用户应用动态灰色模型。关键词:能源政策预测灰色动态决策支持系统灰色预测模型天然气披露声明作者未报告潜在利益冲突伦理批准本文不包括任何作者进行的任何人类参与者或动物研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.80
自引率
12.80%
发文量
42
审稿时长
6-12 weeks
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