Özet
Both estimation and evaluation of electric energy potential from biomass are quite important in terms of renewable energy aims and policies. Identification of suitable locations for biomass energy facilities carries significant benefits from the rich potential for bioenergy. In this context, the paper applies a novel methodology in two study areas, namely Boulder, Colorado, United States (USA) and Selcuklu, Konya, Turkey. First, the study calculates energy potential from animal manure (i.e., cattle and sheep) and agricultural residues (i.e., corn, wheat, and barley). Second, location suitability is obtained by means of a Geographic Information Systems (GIS)-based approach that exploits fuzzy logic and the Best Worst Method (BWM). The result for bioenergy potential shows that Selcuklu (for 2019) and Boulder (for 2017) have 10,834 kW and 1,406 kW installed capacity. Differences in the pattern of suitable locations are also apparent. Selcuklu shows a broad spatial distribution of good but relatively lower suitability scores, while Boulder's scores are more localized and extremely high (approaching 0.99), due to differing patterns of steep terrain and to differing policies regulating green space. This information indicates that the electricity generation potential and facility location suitability for biomass energy clearly differ depending on differences in study area characteristics.
| Orijinal dil | İngilizce |
|---|---|
| Makale numarası | 102626 |
| Dergi | Sustainable Energy Technologies and Assessments |
| Hacim | 53 |
| DOI'lar | |
| Yayın durumu | Yayınlandı - Eki 2022 |
Bibliyografik not
Publisher Copyright:© 2022 Elsevier Ltd
Finansman
The first author of this study is fully supported by the Turkey Council of Higher Education with International Research Scholarships for Research Assistants (YUDAB) during this research. The authors also acknowledge the University of Colorado - Boulder Geography Department for the invitation to the first author to collaborate with faculty and doctoral researchers, as well as access to computing facilities during work on the project. The second author’s work is related to the Grand Challenge Initiative “Earth Lab” at the University of Colorado ( https://www.colorado.edu/earthlab/ ). The second and third authors are partially supported in this research by the U.S. National Science Foundation (NSF Methodology, Measurement & Statistics (MMS) Program, Award No. 1853866). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the four authors and do not necessarily reflect the views of the funding agencies. The first author of this study is fully supported by the Turkey Council of Higher Education with International Research Scholarships for Research Assistants (YUDAB) during this research. The authors also acknowledge the University of Colorado - Boulder Geography Department for the invitation to the first author to collaborate with faculty and doctoral researchers, as well as access to computing facilities during work on the project. The second author's work is related to the Grand Challenge Initiative “Earth Lab” at the University of Colorado (https://www.colorado.edu/earthlab/). The second and third authors are partially supported in this research by the U.S. National Science Foundation (NSF Methodology, Measurement & Statistics (MMS) Program, Award No. 1853866). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the four authors and do not necessarily reflect the views of the funding agencies.
| Finansörler | Finansör numarası |
|---|---|
| University of Colorado - Boulder Geography Department | |
| National Science Foundation | 1853866 |
| University of Colorado |
BM SKH
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