Muhammad Zeeshan conducted research on determining suitable sites for solar and wind energy farms in Pakistan using a combination of GIS and AHP. He developed a comprehensive three scenario framework to assess suitability for 1) utility-scale solar PV farms, 2) utility-scale wind farms, and 3) small-scale solar farms in remote areas. For each scenario, he selected critical criteria from climate, technical, geographical and location factors. He collected and processed spatial data layers for the criteria, applied exclusions and restrictions, used AHP to determine criteria weights, conducted a weighted overlay analysis in GIS, and generated final suitability maps showing optimal sites. The research aims to help accelerate renewable energy development and expand electricity access in Pakistan

1. Abasyn University Islamabad Campus
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2. Research on Site Suitability for
Solar and Wind Energy in
Developing Countries Using
combination of GIS-AHP
Muhammad Zeeshan
7247
Department Electrical Engineering
Abasyn University, Islamabad Campus
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MS Thesis

3. Guidance
Supervisor
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Dr. Ghulam Murtaza Kiyani NUST College of Electrical and
Mechanical Engineering

4. Introduction
• Solar PV and wind energy increasing popularity in developing countries.
•Contribution of multiple factors to efficiency of renewable energy farms.
• Utilization of GIS in power projects.
• MCDA (Multi-Criteria Decision Analysis ) methods for determining solutions to multivariable
problems.
• Pakistan alternative and renewable energy (ARE) policy 2019 [1].
• Only 75% of population have access to electricity in Pakistan [2].
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5. Literature Review
• Similar studies differentiated on the basis of the
i. Scale of area under study
ii. Method used for criteria ranking
iii. Number of criteria considered
iv. Type of renewable energy
• Notable studies include suitability for Solar sites in Kahramanmaras, Turkey using 14 criteria
with AHP [3], suitability for solar sites in Saudi Arabia using 7 criteria with AHP [4], suitability for
wind sites in West Virginia, USA using 10 criteria with AHP [5], suitability for wind and solar sites
in Songkhla, Thailand using 11 criteria with AHP [6].
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6. Literature Review
Research Paper Journal Year Method Renewable Energy
A comprehensive framework based on GIS-AHP for the
installation of solar PV farms in Kahramanmaras¸ , Turkey
Renewable Energy,
Elsevier
2021 AHP Solar PV
GIS based site suitability assessment for wind and solar farms in
Songkhla, Thailand
Renewable Energy,
Elsevier
2018 AHP Solar PV, Wind
Land Suitability Analysis for Solar Farms Exploitation Using GIS
and Fuzzy Analytic Hierarchy Process (FAHP)—A Case Study of
Iran
Energies, MDPI 2016 Fuzzy AHP Solar PV
GIS-based multi-criteria decision analysis of utility-scale
wind farm site suitability in West Virginia
GeoJournal, Springer 2021 AHP Wind
Neural network-based modeling of wind/solar farm siting: a case
study of East-Azerbaijan
International Journal of
Sustainable Energy,
Taylor and Francis
2020 ANN + AHP Wind
Solar power potential of Tanzania: Identifying CSP and PV hot
spots through a GIS multicriteria decision making analysis
Renewable Energy,
Elsevier
2017 AHP Solar PV, Solar CSP
Solar PV power plant site selection using a GIS-AHP based
approach with application in Saudi Arabia
Applied Energy,
Elsevier
2017 AHP Solar PV
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7. Literature Review
• Considerable gap found in studies done for developing countries
• Lack of generalized framework applicable to broad range of studies
• Consideration of excessive criteria
• No scenarios for remote areas in particular
• Lack of published studies done for Pakistan
• Literature review revealed two studies in case of Pakistan
i. Suitable sites for wind farms in specific cities of Pakistan with AHP [7].
ii. Suitability for solar sites in Baluchistan using Zone clustering [8].
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8. Research Objectives
• Formation of a comprehensive framework for site suitability studies in developing countries for
Solar PV and Wind energy.
• Consideration of absolute critical criteria
• Sites suitability for far-off areas potentially devoid of access to electricity infrastructure.
• Case study of Pakistan as a developing country
• Three scenario based framework
i. Utility scale Solar PV farms sites
ii. Utility scale Wind energy farms sites
iii. Small scale solar PV farms sites
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9. Methodology
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10. Methodology
Utility Scale Solar Energy Farm Sites Utility Scale Wind Energy Farm Sites Small Scale Solar Sites (far-off areas)
GHI
Avg Temp
Slope
Land cover
Land aspect
Proximity to Roads
Proximity to Cities
Proximity to Power Lines
Wind speed
Wind Power Density (WPD)
Elevation
Slope
Land cover
Proximity to Roads
Proximity to Cities
Proximity to Power Lines
Distance from Substations
Distance from Settlements
Distance from Small Cities
Distance from Major Cities
Distance from Roads
GHI
Average Temperature
Slope
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Criteria selection
• Sub-criteria chosen from the main criteria of Climate, Technical, Orography and Location.
• 8 critical sub-criteria selected for each scenario

11. Methodology
Data collection
• Data obtained in two forms.
i. Raster files for climate and orographic data maps
ii. Shape files for infrastructural and locational maps
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Datasets Source
GHI and Average Temperature Solar GIS [9]
Wind Speed and Wind Power Density Global Wind Atlas [10]
Land Cover GLOBECOVER [11]
Location and Infrastructure NREL [12]
Wild life Protected zones UNEP [13]
Settlements/ Population Density World Pop [14]

12. Methodology
For criteria maps processing, ArcGIS 10.7 was used
Data Processing
• Raster datasets were resampled, clipped and projected
• Slope and Land Aspect maps layers obtained by geoprocessing tools
• Euclidean Distance tool utilized to find out the proximity
• Restriction map obtained by merging all restricted criteria parameters
Reclassification
• Restriction criteria map conversion to binary scale of 0 and 1.
• Reclassification of criteria maps on a linear scale of 1 – 5.
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13. Methodology
Restrictions and Exclusions
• Exclusions were zones deemed
unsuitable for further consideration
• 26.77% of total area excluded from
study.
• Restrictions included scenario specific
limits on certain criteria.
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14. Methodology
Analytical Hierarchy Process (AHP)
• Used for complex multivariable problem based on user
input and understanding .
• Alternatives distinguished on the basis of factors or
criteria.
• Comparison matrix formation
• Criteria valued on intensity of importance by a scale of 1 -
9 depending on relative importance.
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15. Methodology
Analytical Hierarchy Process (AHP)
• Consistency analyzed via random consistency index (RI)
which gives consistency ratio (CR)
• If consistency ratio is below the threshold of 0.10, results
are considered consistent enough.
• For determining priority weights, AHP extension in ArcGIS
was utilized.
• Final consistency ratios were 0.029, 0.056 and 0.049 for
scenario 1, 2 and 3 respectively.
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Utility Scale Solar PV Farms
C1 C2 C3 C4 C5 C6 C7 C8
C1 1 2 3 4 5 8 7 6
C2 1/2 1 2 3 4 7 6 5
C3 1/3 1/2 1 2 3 6 5 4
C4 1/4 1/3 1/2 1 2 5 4 3
C5 1/5 1/4 1/3 1/2 1 4 3 2
C6 1/8 1/7 1/6 1/5 1/4 1 1/2 1/3
C7 1/7 1/6 1/5 1/4 1/3 2 1 1/2
C8 1/6 1/5 1/4 1/3 1/2 3 2 1

16. Methodology
Utility Scale Solar Energy Farm Sites Utility Scale Wind Energy Farm Sites Small Scale Solar Sites (far-off areas)
GHI
Average Temperature
Slope
Land cover
Land aspect
Proximity to Roads
Proximity to Cities
Proximity to Power Lines
0.3268
0.2273
0.1569
0.0734
0.1077
0.0340
0.0242
0.0498
Wind Speed
Wind Power Density (WPD)
Elevation
Slope
Land cover
Proximity to Roads
Proximity to Cities
Proximity to Power Lines
0.3367
0.2400
0.1138
0.0722
0.1290
0.0417
0.0238
0.0498
Distance from Substations
Distance from Settlements
Distance from Small Cities
Distance from Major Cities
Distance from Roads
GHI
Average Temperature
Slope
0.3155
0.2178
0.1789
0.1184
0.0696
0.0457
0.0315
0.0222
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Analytical Hierarchy Process (AHP)
• Higher priority to climate and orography in utility scale cases.
• Higher priority to locational criteria in small scale solar PV case.

17. Methodology
Weighted Overlay
• Allocation of priority weight obtained by AHP to each criteria map.
• Recombination of each criteria map.
• Initial output map ranked based on final score according to priority weight.
Exclusion of Restricted areas
• Algebraic multiplication of initial suitability map with excluded zones map.
• Final suitability map for each scenario contained sites based on suitability scale
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18. Future Work
• Inclusion of existing fossil fuel power plants.
• Combination of other renewable technologies .
• Country specific criteria can be considered such as natural occurrences.
• Use of updated and paid datasets.
• Opinions from stake holders and industry experts and investors.
• Other MCDA methods to enhance this study and comparison of results.
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19. References
[1] “Pakistan - Renewable Energy.” https://www.trade.gov/country-commercial-guides/pakistan-renewable-energy (accessed Jun 2023).
[2] H. Ritchie and M. Roser, “Energy,” Our World Data, Nov. 2020, Accessed: Jan. 16, 2022. [Online]. Available: https://ourworldindata.org/energy.
[3] M. A. Günen, “A comprehensive framework based on GIS-AHP for the installation of solar PV farms in Kahramanmaraş, Turkey,” Renew. Energy, vol. 178, pp.
212–225, Nov. 2021, doi: 10.1016/j.renene.2021.06.078.
[4] H. Z. Al Garni and A. Awasthi, “Solar PV power plant site selection using a GIS-AHP based approach with application in Saudi Arabia,” Appl. Energy, vol. 206,
pp. 1225–1240, Nov. 2017, doi: 10.1016/j.apenergy.2017.10.024.
[5] B. A. Ajanaku, M. P. Strager, and A. R. Collins, “GIS-based multi-criteria decision analysis of utility-scale wind farm site suitability in West Virginia,” GeoJournal,
2021, doi: 10.1007/s10708-021-10453-y.
[6] S. Ali, J. Taweekun, K. Techato, J. Waewsak, and S. Gyawali, “GIS based site suitability assessment for wind and solar farms in Songkhla, Thailand,” Renew.
Energy, vol. 132, pp. 1360–1372, Mar. 2019, doi: 10.1016/j.renene.2018.09.035.
[7] Y. Ali, M. Butt, M. sabir, U. Mumtaz, and A. Salman, “Selection of suitable site in Pakistan for wind power plant installation using analytic hierarchy process
(AHP),” Journal of Control and Decision, vol. 5, no. 2. Taylor and Francis Ltd., pp. 117–128, Apr. 03, 2018, doi: 10.1080/23307706.2017.1346490.
[8] F. Amjad and L. A. Shah, “Identification and assessment of sites for solar farms development using GIS and density based clustering technique- A case of
Pakistan,” Renew. Energy, vol. 155, pp. 761–769, 2020, doi: 10.1016/j.renene.2020.03.083.
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20. References
[9] “Solar resource maps and GIS data for 200+ countries | Solargis.” https://solargis.com/maps-and-gis-data/download/pakistan (accessed Jan. 19, 2022).
[10] “Global Wind Atlas.” https://globalwindatlas.info/download/gis-files (accessed Jan. 19, 2022).
[11] “ESA Data User Element.” http://due.esrin.esa.int/page_globcover.php (accessed Jan. 19, 2022).
[12] “RE Data Explorer.” https://www.re-explorer.org/re-data-explorer/download/intro (accessed Jan. 19, 2022).
[13] “Explore the World’s Protected Areas.” https://www.protectedplanet.net/country/PAK (accessed Jan. 19, 2022).
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21. Abasyn University, Department of Electrical Engineering
THANK YOU
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