Journals / International Journal of Environment and Geoinformatics / 2019 / Cilt: 6 - Sayı: 3

Geospatial Evaluation of Wind Energy Potential in the SE and SS of Nigeria

Pages
244–253
Publication Date
2022-10-19
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results indicate the presence of a reasonable amount of potential forwind energy, which lies mostly in the southernmost part of the study area.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Investment into a renewable energy project spurs the need to investigate sites with potential for a renewable energy source.
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Key Findings & Data:A multi-criteria decision analysis (MCDA) model was implemented usingLandsat TM images at bands 2, 3 and 4, and integrated with NASA global wind speed data, airport location map and forest reservemap of the area.
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Conclusion & Impact:The results indicate the presence of a reasonable amount of potential forwind energy, which lies mostly in the southernmost part of the study area.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

Investment into a renewable energy project spurs the need to investigate sites with potential for a renewable energy source. Such acrucial investigation is the main motivation for this study, which uses a geospatial technology to evaluate wind energy potential withinthe south-east (SE) and south-south (SS) regions of Nigeria. A multi-criteria decision analysis (MCDA) model was implemented usingLandsat TM images at bands 2, 3 and 4, and integrated with NASA global wind speed data, airport location map and forest reservemap of the area. The criteria for generation of wind energy potential map were wind speed ≥ 3m/s, 2000m buffer from built-up areas,2,500m buffer from airports and outside the forest reserve. The results indicate the presence of a reasonable amount of potential forwind energy, which lies mostly in the southernmost part of the study area. The total potential area is about 104,700 hectares in landsize, which is merely 1.2% of the total study area, although River state encloses most of the potential locations. When compared toglobal vortex wind data, by visual inspection, these potential areas show a great deal of sensitivity to wind speed, highlighting itscritical importance in the present modelling. Wind farms can be located in this area, although it is a rather small-scale investment in arenewable energy resource considering that the consumable amount of energy in the study area is in a steady increase. Stakeholdersand experts in energy economy will find that the need to protect this potential energy location from indiscriminate urban developmentand other anthropogenic activities is compelling.

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Cite This Article

NKWUNOOWO, U. C., CHIEMELU, N. E., OKEKE, F. I., OJINNAKA, O. C. (2022). Geospatial Evaluation of Wind Energy Potential in the SE and SS of Nigeria. International Journal of Environment and Geoinformatics, Cilt: 6 - Sayı: 3, 244–253. https://ajindex.com/articles/541036

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References (12)

  1. Agbetuyi, AF., Odigwe, IA., Awelewa, AA. Awosope, CO. (2013). Wind power potential and integration in Africa. International Journal of Development and Sustainability, 2(1), 232-239.
  2. Ahlborg, H., Hammar, L. (2014). Drivers and barriers to rural electrification in Tanzania and Mozambique– Grid-extension, off-grid, and renewable energy technologies. Renewable Energy, 61, 117-124.
  3. Akuru, UB., Onukwube, IE., Okoro, OI., Obe, ES. (2017). Towards 100% renewable energy in Nigeria. Renewable and Sustainable Energy Reviews, 71, 943- 953. Aslani, A. Wong, KFV. (2014). Analysis of renewable energy development to power generation in the United States. Renewable Energy, 63, 153-161.
  4. Aydın, NY., Kentel, E. Düzgün, S. (2010). GIS-based environmental assessment of wind energy systems for spatial planning: A case study from Western Turkey. Renewable and Sustainable Energy Reviews, 14(1), 364-373.
  5. Aydın, NY. (2009). GIS-Based Site Selection Approach for Wind and Solar Energy Systems: A case study from Western Turkey. Ayodele, TR., Ogunjuyigbe, ASO. Amusan, TO. (2016). Wind power utilization assessment and economic analysis of wind turbines across fifteen locations in the six geographical zones of Nigeria. Journal of cleaner production, 129, 341-349.
  6. Baban, SMJ., Parry, T. (2001). Developing and applying a GIS-assisted approach to locating wind farms in the UK. Renewable Energy, 24, 59-71.
  7. Barry, ML., Steyn, H. Brent, A. (2011). Selection of renewable energy technologies for Africa: Eight case studies in Rwanda, Tanzania and Malawi. Renewable Energy, 36(11), 2845-2852.
  8. Cevallos-Sierra, J., Ramos-Martin, J. (2018). Spatial assessment of the potential of renewable energy: The case of Ecuador. Renewable and Sustainable Energy Reviews, 81, 1154-1165.
  9. Clarke, A. (1991). Wind energy progress and potential. Energy Policy, 19, 742-755.
  10. Connolly, D., Lund, H., Mathiesen, BV. (2016). Smart Energy Europe: The technical and economic impact of one potential 100% renewable energy scenario for the European Union. Renewable and Sustainable Energy Reviews, 60, 1634-1653.
  11. Davidson, MR., Zhang, D., Xiong, W., Zhang, X., Karplus, VJ. (2016). Modelling the potential for wind energy integration on China’s coal-heavy electricity grid. Nature Energy, 1(7), 16086. Ellabban, O., Abu-Rub, H., Blaabjerg, F. (2014). Renewable energy resources: Current status, future rospects and their enabling technology. Renewable and Sustainable Energy Reviews, 39, 748-764.
  12. Frondel, M., Ritter, N., Schmidt, C.M. Vance,