Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/46352
Title: Forecasting the biomass-based energy potential using artificial intelligence and geographic information systems: A case study
Authors: Senocak, Ahmet Alp
Goren, Hacer Guner
Keywords: Biomass
Renewable energy
Forecasting
Geographic information systems
Artificial intelligence
Crop Residues
Bioenergy
Availability
Gis
Resource
Publisher: Elsevier - Division Reed Elsevier India Pvt Ltd
Abstract: To meet the energy demand in a sustainable way, fossil fuels must be substituted with alternative resources and technologies. This transformation is encouraged to reduce greenhouse gases using environmental-friendly practices. Although our country is rich in biomass resources due to climate, land conditions, agriculture and animal husbandry activities, the installed power is quite below its potential. Focusing on this point, the aim of this study is to propose a forecasting method that determines the quantities, distributions, production amounts, waste amounts and energy potential of various biomass resources consistently. The integrated method used in the solution utilizes statistical data and consists of artificial intelligence and geographic information systems. First of all, various bioenergy sources that can be used as energy resources have been determined, and the amount, yield, and energy potential of animal and agricultural wastes expected to occur in the following years have been estimated using an artificial intelligence-based method, support vector regression. Then, spatial analysis has been carried out using geographic information systems, and the distribution of existing and possible agricultural lands has been determined. Finally, the amount of energy that can be obtained using wastes from different biomass sources under various scenarios has been calculated and solutions have been compared. To the best of our knowledge, this study is the first proposing an integrated method consisting of support vector regression and geographic information systems to forecast the biomass-based energy potential in Turkey. The integrated method was applied to Acipayam district in Denizli. Among the various scenario approaches, the cultivation of rapeseed (canola) plants on non-utilized arable land and the use of its wastes in bioenergy production have been found to yield the highest energy potential. The results showed that approximately 29,2%, 27,8%, and 27,6% energy increase could be obtained from agricultural residues of rapeseed in the next three years if it was planted on the quarter of the idle land. Besides, under this scenario, the total annual electricity demand of 6972, 6663 and 6545 houses could be met from agricultural residues in a sustainable and clean manner. The proposed method can be applied to different regions, various biomass resources and used to make strategic decisions in this field. (c) 2021 Karabuk University. Publishing services by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
URI: https://doi.org/10.1016/j.jestch.2021.04.011
https://hdl.handle.net/11499/46352
ISSN: 2215-0986
Appears in Collections:Mühendislik Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Files in This Item:
File SizeFormat 
1-s2.0-S2215098621001014-main.pdf1.77 MBAdobe PDFView/Open
Show full item record



CORE Recommender

SCOPUSTM   
Citations

24
checked on Oct 13, 2024

WEB OF SCIENCETM
Citations

18
checked on Dec 19, 2024

Page view(s)

82
checked on Aug 24, 2024

Download(s)

64
checked on Aug 24, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.