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Suitability Analysis of Solar Photovoltaic Farm Locations Using GIS: A Case Study of Nakuru County, Kenya

Publication date: 19.09.2024

Geoinformatica Polonica, 2024, Vol. 23 (2024), pp. 7 - 15

https://doi.org/10.4467/21995923GP.24.001.20196

Authors

,
Wiso Vincent
University of Nairobi
, Kenya
https://orcid.org/0009-0009-0312-4221 Orcid
Contact with author
All publications →
John Bosco Kyalo Kiema
University of Nairobi
, Kenya
https://orcid.org/0009-0006-8113-6808 Orcid
Contact with author
All publications →

Titles

Suitability Analysis of Solar Photovoltaic Farm Locations Using GIS: A Case Study of Nakuru County, Kenya

Abstract

Renewable energy sources play a crucial role in reducing global reliance on fossil fuels. Advancements in technology has en- abled harnessing of renewable energy from solar, wind, and ocean tides to be viable. Solar energy, in particular, has gained significant global recognition as a renewable energy alternative. This study integrates Multi-Criteria Evaluation (MCE) and Geographic Information Systems (GIS) to assess Solar Photovoltaic Farms (SPVFs) suitability in Nakuru County, Kenya.

The study considered seven criteria including; slope, solar radiation, aspect, land use land cover, proximity to roads, power transmission lines, and settlements. These were evaluated using the Analytical Hierarchy Process (AHP) to generate weights for each decision criterion. The weights were used to overlay independent criteria maps that were formed as a result of the re- classification of each criterion from which a composite rated map was developed. Similarly, a composite restriction map was created by leveraging on constraint criteria including; protected ecosystems, water bodies, settlement areas, slope over 20%, proximity to roads, proximity to the transmission line, and land use land cover.

Results obtained from overlaying the composite rated and restricted maps reveal Nakuru County’s general suitability for SPVFs, except for Kuresoi North and Kuresoi South divisions which exhibit low solar radiation. Extremely-suitable areas ac- counted for 3.00% (224.14 km²), very-suitable areas 34.05% (2541.45 km2), moderately-suitable areas 7.76% (579.55 km2), marginally-suitable areas 1.47% (109.77 km2) while least-suitable areas covered 0.02% (1.39 km2).

The study provides valuable data and information for government agencies and investors to identify potential Photovoltaic (PV) system sites. Furthermore, the government is encouraged to establish a favorable framework for solar PV exploration and provide incentives to the private sector to facilitate the establishment of SPVFs.

References

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1. Kenya National Bureau of Statistics. https://www.knbs.or.ke/, 2022.

2. Takase, M., Kipkoech, R., Essandoh, P.K. A comprehensive review of energy scenario and sustainable energy in Kenya. Fuel Communications, (https://doi.org/10.1016/J.JFUE-CO.2021.100015), 2021; volume 7, 100015, pp. 1–13.

3. Aronoff, S. Geographic Information Systems: A Management Perspective. WDL Publication, Ottawa, Canada, 1989.

4. Longley, P.A., Goodchild, M., Maguire, D.J., Rhind, D. Geographic Information Science and Systems. Hoboken, NJ: Wiley, 2015.

5. Awange, L.J., Kiema, J.B.K. Environmental Geoinformatics: Monitoring and Management (Environmental Science and Engineering). 2013th Edition. Springer-Verlag, Berlin Heidelberg, 541 (https://doi.org/10.1007/978-3-642-34085-7), 2013.

6. Villacreses, G., Gaona, G., Martínez-Gómez, J., Jijón, D.J. Wind farms suitability location using geographical information system (GIS), based on multi-criteria decision making (MCDM) methods: The case of continental Ecuador. Renewable Energy, 2017; volume 109, pp. 275–286.

7. Huang, I.B., Keisler, J., Linkov, I. Multi-criteria decision analysis in environmental sciences: Ten years of applications and trends. Science of The Total Environment (https://doi.org/10.1016/J.SCITOTENV.2011.06.022), 2011; volume 409(19), pp. 3578–3594.

8. Ukwishaka, D., Mwizerwa, F., Hakizimana, J. Geospatial Analysis of Site Suitability for Solar Photovoltaic (PV) in Rwanda. Rwanda Journal of Engineering, Science, Technology and Environment, (https://dx.doi.org/10.4314/rjeste.v4i1.3S), 2021; volume 4, pp. 2617–2321.

9. Oloo, F., Olang, L., Strobl, J. Spatial modeling of solar energy potential in Kenya. Int. J. Sustain. Energy Plan. Manag., (http://doi.org/10.5278/ijsepm.2015.6.3), 2015; volume 6, 17–30.

10. Nakuru CIDP. Nakuru County Integrated Development Plan (2018–2022). (https://nakuru.go.ke/wp-content/uploads/2021/11/3.-NAKURU-CIDP-2018-2022-FINAL.-copy.pdf).

11. Vrînceanu, A., Grigorescu, I., Dumitrașcu, M., Mocanu, I., Dumitrică, C., Micu, D., Kucsicsa, G., Mitrică, B. Impacts of Photovoltaic Farms on the Environment in the Romanian Plain. Energies (https://doi.org/10.3390/en12132533), 2019; volume 12, pp. 1–18.

12. Breeze, P. Solar Power. Power Generation Technologies (https://doi.org/10.1016/B978-0-08-102631-1.00013-4), 2019, pp. 293–321.

13. Shahsavari, A., Akbari, M. The potential of solar energy in developing countries for reducing energy-related emissions. Renewable and Sustainable Energy Reviews, (https://doi.org/10.1016/J.RSER.2018.03.065), 2018; volume 90, pp. 275–291.

14. Noorollahi, Y., Senani, A. G., Fadaei, A., Simaee, M., Moltames, R. A framework for GIS-based site selection and technical potential evaluation of PV solar farm using Fuzzy-Boolean logic and AHP multi-criteria decision-making approach. Renewable Energy (https://doi.org/10.1016/j.renene.2021.12.124), 2022; volume 186, pp. 89–104.

15. Sarkodie, S.A., Owusu, P.A. Carbon dioxide emissions, GDP, energy use and population growth: A multivariate and causality analysis for Ghana. Environmental Science and Pollution Research International (doi:1007/s11356-016- 6511-x), 2016, pp. 1971–2013

16. Owiro, D., Poquillon, G., Njonjo, K. S., Oduor, C. Situational analysis of energy industry, policy, and strategy for Kenya. Institute of Economic Affairs, 8, 2015.

17. Marigi, S.N. Climate Change Vulnerability and Impacts Analysis in Kenya. American Journal of Climate Change (https://doi.org/10.4236/ajcc.2017.61004), 2017; volume 6, pp. 52–74.

18. Ndungu, L.W., Kiema, J.B.K., Siriba, D.N. Insights from Tracking Thirty Years of Change in Agro Ecologies of Lower Eastern Kenya. East African Agricultural and Forestry Journal, 2022; volume 86, no. 3 & 4, pp. 152–179.

19. Sarkodie, S.A., Adom, P.K. Determinants of energy consumption in Kenya: A NIPALS approach (https://doi.org/10.1016/j.energy.2018.06.195), 2018; volume 159, no. 15, pp. 696–705.

Information

Information: Geoinformatica Polonica, 2024, Vol. 23 (2024), pp. 7 - 15

Article type: Original article

Titles:

English: Suitability Analysis of Solar Photovoltaic Farm Locations Using GIS: A Case Study of Nakuru County, Kenya
Polish: Analiza przydatności lokalizacji farm fotowoltaicznych z wykorzystaniem GIS: Studium przypadku hrabstwa Nakuru, Kenia

Authors

Published at: 19.09.2024

Article status: Open

Licence: CC BY  licence icon

Percentage share of authors:

Wiso Vincent (Author) - 50%
John Bosco Kyalo Kiema (Author) - 50%

Information about author:

Wiso Vincent – University of Nairobi, Department of Geospatial and Space Technology

John Bosco Kyalo Kiema – University of Nairobi, Department of Geospatial and Space Technology

Article corrections:

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Publication languages:

English