Forecasting Natural Gas Consumption in the US Power Sector by a Randomly Optimized Fractional Grey System Model

Natural gas is one of the main energy resources for electricity generation. Reliable forecasting is vital to make sensible policies. A randomly optimized fractional grey system model is developed in this work to forecast the natural gas consumption in the power sector of the United States. The nonho...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Yubin Cai, Xin Ma, Wenqing Wu, Yanqiao Deng
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/bb916bc7796d4acfa57a057a38b80d2b
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:bb916bc7796d4acfa57a057a38b80d2b
record_format	dspace
spelling	oai:doaj.org-article:bb916bc7796d4acfa57a057a38b80d2b2021-11-22T01:10:51ZForecasting Natural Gas Consumption in the US Power Sector by a Randomly Optimized Fractional Grey System Model1563-514710.1155/2021/5541650https://doaj.org/article/bb916bc7796d4acfa57a057a38b80d2b2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/5541650https://doaj.org/toc/1563-5147Natural gas is one of the main energy resources for electricity generation. Reliable forecasting is vital to make sensible policies. A randomly optimized fractional grey system model is developed in this work to forecast the natural gas consumption in the power sector of the United States. The nonhomogeneous grey model with fractional-order accumulation is introduced along with discussions between other existing grey models. A random search optimization scheme is then introduced to optimize the nonlinear parameter of the grey model. And the complete forecasting scheme is built based on the rolling mechanism. The case study is executed based on the updated data set of natural gas consumption of the power sector in the United States. The comparison of results is analyzed from different step sizes, different grey system models, and benchmark models. They all show that the proposed method has significant advantages over the other existing methods, which indicates the proposed method has high potential in short-term forecasting for natural gas consumption of the power sector in United States.Yubin CaiXin MaWenqing WuYanqiao DengHindawi LimitedarticleEngineering (General). Civil engineering (General)TA1-2040MathematicsQA1-939ENMathematical Problems in Engineering, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939
spellingShingle	Engineering (General). Civil engineering (General) TA1-2040 Mathematics QA1-939 Yubin Cai Xin Ma Wenqing Wu Yanqiao Deng Forecasting Natural Gas Consumption in the US Power Sector by a Randomly Optimized Fractional Grey System Model
description	Natural gas is one of the main energy resources for electricity generation. Reliable forecasting is vital to make sensible policies. A randomly optimized fractional grey system model is developed in this work to forecast the natural gas consumption in the power sector of the United States. The nonhomogeneous grey model with fractional-order accumulation is introduced along with discussions between other existing grey models. A random search optimization scheme is then introduced to optimize the nonlinear parameter of the grey model. And the complete forecasting scheme is built based on the rolling mechanism. The case study is executed based on the updated data set of natural gas consumption of the power sector in the United States. The comparison of results is analyzed from different step sizes, different grey system models, and benchmark models. They all show that the proposed method has significant advantages over the other existing methods, which indicates the proposed method has high potential in short-term forecasting for natural gas consumption of the power sector in United States.
format	article
author	Yubin Cai Xin Ma Wenqing Wu Yanqiao Deng
author_facet	Yubin Cai Xin Ma Wenqing Wu Yanqiao Deng
author_sort	Yubin Cai
title	Forecasting Natural Gas Consumption in the US Power Sector by a Randomly Optimized Fractional Grey System Model
title_short	Forecasting Natural Gas Consumption in the US Power Sector by a Randomly Optimized Fractional Grey System Model
title_full	Forecasting Natural Gas Consumption in the US Power Sector by a Randomly Optimized Fractional Grey System Model
title_fullStr	Forecasting Natural Gas Consumption in the US Power Sector by a Randomly Optimized Fractional Grey System Model
title_full_unstemmed	Forecasting Natural Gas Consumption in the US Power Sector by a Randomly Optimized Fractional Grey System Model
title_sort	forecasting natural gas consumption in the us power sector by a randomly optimized fractional grey system model
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/bb916bc7796d4acfa57a057a38b80d2b
work_keys_str_mv	AT yubincai forecastingnaturalgasconsumptionintheuspowersectorbyarandomlyoptimizedfractionalgreysystemmodel AT xinma forecastingnaturalgasconsumptionintheuspowersectorbyarandomlyoptimizedfractionalgreysystemmodel AT wenqingwu forecastingnaturalgasconsumptionintheuspowersectorbyarandomlyoptimizedfractionalgreysystemmodel AT yanqiaodeng forecastingnaturalgasconsumptionintheuspowersectorbyarandomlyoptimizedfractionalgreysystemmodel
_version_	1718418365106618368

Forecasting Natural Gas Consumption in the US Power Sector by a Randomly Optimized Fractional Grey System Model

Ejemplares similares