GIS-Based Site Suitability Analysis for Solar Power Systems in Mongolia
Source abstract
Abstract
In this study, we employed a geographic information system (GIS)-based approach to identify sites suitable for large-scale solar photovoltaic (PV) power plant installations in Mongolia. Accordingly, cells of 30 × 30 m were used, and data based on seven criteria, including annual global horizontal radiation, annual average temperature, elevation, slope, slope direction (aspect), and distances from main roads and major power lines, were collected for each cell. GIS layers for these seven criteria were then converted into rated value layers using four grades. The weightings applied to the seven criteria were determined, using an analytical hierarchy process, by ten solar field experts. By combining the seven rating value layers with the weightings, a site suitability map was developed, using good, fair, low, and poor suitability grades. The results showed that sites graded as good, fair, low, and poor accounted for 3.27%, 53.06%, 42.59%, and 1.08% of the total surface area, respectively. Good sites were predominantly located in the southern and central regions of Mongolia. As the current demand for electric power in southern and central regions is low and high, respectively, we concluded that the central region of Mongolia should be prioritized for installing PV power plants.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Soil and Land Suitability Analysis · Solar Radiation and Photovoltaics · Multi-Criteria Decision Making
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Energy Resources Engineering, Pukyong National University, Busan 48513, Korea
Funding
Korea Institute of Energy Technology Evaluation and Planning
References (31)
Show source-provided references
1. (2021, February 25). U.S. Energy Information Administration, Available online: https://www.eia.gov/todayinenergy/detail.php?id=41433/.
2. The evaluation of solar farm locations applying Geographic Information System and Multi-Criteria Decision-Making methods: Case study in southern Morocco10.1016/j.rser.2015.07.054 ↗
3. (2021, February 25). Global Energy Institute. Available online: https://www.globalenergyinstitute.org/look-ieas-new-global-energy-forecast/.
4. Rating of roofs surfaces regarding their solar potential and suitability for PV systems, based on LiDAR data10.1016/j.apenergy.2012.08.042 ↗
5. Solar PV power plant site selection using a GIS-AHP based approach with application in Saudi Arabia10.1016/j.apenergy.2017.10.024 ↗
6. PV Analyst: Coupling ArcGIS with TRNSYS to assess distributed photovoltaic potential in urban areas10.1016/j.solener.2011.08.034 ↗
7. Choi, Y., Suh, J., and Kim, S.-M. (2019). GIS-Based Solar Radiation Mapping, Site Evaluation, and Potential Assessment: A Review. Appl. Sci., 9.10.3390/app9091960 ↗
8. GIS-based multicriteria decision analysis: A survey of the literature
9. GIS-based solar farms site selection using analytic hierarchy process (AHP) in Karapinar region, Konya/Turkey10.1016/j.rser.2013.07.042 ↗
10. Potential of Concentrated Solar Power (CSP) in Zimbabwe10.1016/j.esd.2014.07.006 ↗
11. Regional Scale wind farm and solar farm suitability assessment using GIS-assisted multi-criteria evaluation10.1016/j.landurbplan.2015.02.001 ↗
12. Solar power potential of Tanzania: Identifying CSP and PV hot spots through a GIS multicriteria decision making analysis10.1016/j.renene.2017.05.077 ↗
13. GIS-based assessment of photovoltaic (PV) and concentrated solar power (CSP) generation potential in West Africa10.1016/j.rser.2017.06.021 ↗
14. Large scale PV sites selection by combining GIS and Analytical Hierarchy Process. Case study: Eastern Morocco10.1016/j.renene.2017.10.044 ↗
15. Developing a GIS-based Fuzzy AHP Model for Selecting Solar Energy Sites in Shodirwan Region in Iran10.14257/ijast.2014.68.04 ↗
16. Noorollahi, E., Fadai, D., Shirazi, M.A., and Ghodsipour, S.H. (2016). Land Suitability Analysis for Solar Farms Exploitation Using GIS and Fuzzy Analytic Hierarchy Process (FAHP)-A Case Study of Iran. Energies, 9.10.3390/en9080643 ↗
17. Suh, J., and Brownson, J.R.S. (2016). Solar farm suitability using geographic information system fuzzy sets and analytic hierarchy processes: Case study of Ulleung Island, Korea. Energies, 9.10.3390/en9080648 ↗
18. Geographical Information Systems (GIS) and Multi-Criteria Decision Making (MCDM) methods for the evaluation of solar farms locations: Case study in south-eastern Spain10.1016/j.rser.2013.03.019 ↗
19. (2021, February 25). Wikipedia. Available online: https://en.wikipedia.org/wiki/Mongolia.
20. (2021, February 25). Energypedia. Available online: https://energypedia.info/wiki/Mongolia_Energy_Situation/.
21. (2021, February 25). Mongolian Ministry of Energy, Available online: http://energy.gov.mn/c/1129.
22. (2021, February 25). Energy Regulatory Commission, Available online: https://erc.gov.mn/web/mn/print/337?date=true.
23. (2021, February 25). Legalinfo. Available online: https://www.legalinfo.mn/annex/details/3220?lawid=6485/.
24. (2021, February 25). Global Solar Atlas. Available online: https://globalsolaratlas.info/download/mongolia/.
25. (2021, February 25). National Agency Meteorology and the Environmental Monitoring, Available online: http://tsag-agaar.gov.mn/atmosphere/.
26. Batchuluun, E., Ymchaa, G., Ser-Od, T., Tsendsuren, T., and Odmandah, L. (2019). Geography VIII, Munkhiin Useg LLC. [2nd ed.].
27. PV site suitability analysis using GIS-based spatial fuzzy multi-criteria evaluation10.1016/j.renene.2010.10.037 ↗
28. How to make a decision: The analytic hierarchy process10.1016/0377-2217(90)90057-I ↗
29. Decision making with the analytic hierarchy process
30. (2021, February 25). Energy Regulatory Commission, Available online: https://erc.gov.mn/web/mn/.
31. (2021, February 25). National Statistics Office of Mongolia. Available online: http://www.nso.mn/.