Forecasting of daily natural gas consumption on regional basis in Turkey using various computational methods
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Date
2013
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier Science Sa
Access Rights
info:eu-repo/semantics/closedAccess
Abstract
It is widely accepted that natural gas is a clean energy source that can be used to meet energy demand for heating and industrial purpose among the fossil fuels and its usage remarkably increases in order to maintain a clean environment in many countries in the world. It is fact that this makes energy investment planning in a country or region highly important for suitable economic development as well as environmental aspect. Therefore, energy demand for various sectors should be estimated in the frame of short-term energy policy. For accurate estimation of short-term energy demand a limited number of computational methods are employed by using the 4 yearly measured natural gas consumption values. Among these methods, the ANN and time series are widely used for short-term estimation of natural gas consumption in Turkey's certain regions. In this study, multilayer perceptron the ANNs with time series approach is proposed to forecast short-term natural gas consumption. Meteorological data (moisture, atmospheric pressure, wind speed and ambient temperature) obtained from the regional gas distribution company and the local meteorology office in last 4 years to construct well-tuned algorithm. Although the number of data was small, the proposed algorithm works well to forecast the short-term natural gas consumption and produces encouraging and meaningful outcomes for future energy investment policy. (C) 2012 Elsevier B.V. All rights reserved.
Description
Taspinar, Fatih/0000-0002-5908-8188
WOS: 000314378500003
WOS: 000314378500003
Keywords
Natural gas consumption, Forecasting methodology, Time series models, SARIMAX, Neural networks
Journal or Series
Energy And Buildings
WoS Q Value
Q1
Scopus Q Value
Q1
Volume
56
