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The site selection of wind energy power plant using GIS-multi-criteria evaluation from economic perspectives.
- Source :
-
Renewable & Sustainable Energy Reviews . Oct2022, Vol. 168, pN.PAG-N.PAG. 1p. - Publication Year :
- 2022
-
Abstract
- The use of wind turbines can help progress towards economic and technological development, lower rates of fossil fuel consumption, decreased greenhouse emissions, and reduced side-effects of climate change. A successful mechanism for developing renewable energy worldwide is the guaranteed purchase of electricity generated from renewable energy sources. Accordingly, this study aims to integrate Geographic Information System-based Multi-criteria Evaluation (GIS-MCE) models with economic frameworks to estimate the optimal purchasing price for electricity produced by wind turbines. A total of 13 criteria maps were used and integrated using Ordered Weighted Averaging (OWA) as a type of MCE model. The criteria were initially normalized based on the minimum, and maximum values and weights were assigned to each criterion, using the Best-Worst method. The OWA model identified optimal site locations at various decision risk levels. The economic efficiency of wind turbines and the potential purchasing price of electricity from turbines were also assessed in terms of Net Present Value (NPV). The results show that Ardabil and Southern Khorasan provinces had the most significant areas in the very-suitable class for wind turbine installation (small/large scale). The purchasing prices for wind-generated electricity ranged from 0.047 to 0.182 US$ for large wind farms and 0.074 to 0.384 US$ for small wind plants. The highest electricity produced from large wind farms was found in Maragheh. • This paper presents a GIS-MCE model to assess the suitability of locations for wind power plants. • It shows a GIS-MCE-based economic model for price estimation of wind energy generated electricity. • The study integrates expert weights, criteria maps, and risk degrees in the price estimation model. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13640321
- Volume :
- 168
- Database :
- Academic Search Index
- Journal :
- Renewable & Sustainable Energy Reviews
- Publication Type :
- Academic Journal
- Accession number :
- 159038942
- Full Text :
- https://doi.org/10.1016/j.rser.2022.112778