Optimizing photovoltaic power plant site selection using analytical hierarchy process and density-based clustering – Policy implications for transmission network expansion, Ghana

Abstract

Despite the enormous solar energy resource in Ghana, the country is yet to fully take advantage of this resource to meet the country’s growing energy demand. Some studies have partly associated this to the lack of appropriate data on the country’s renewable energy potentials. This study proposed a new approach in selecting appropriate sites for the development of solar farms by combining the Analytical Hierarchical Process and Density-Based Clustering using a Geographic Information System. The study identifies suitable clusters and ranks them for the development of solar photovoltaic farms. Wa in the Upper West region, which is macro cluster 1 in this study, is ranked as the top-most priority. It has approximately 264 km2 and a mean annual Global Horizontal Irradiance (GHI) of 1998.55 kWh/m2*year. Macro cluster 3 comes as the second priority, with a mean annual GHI of 1985.69 kWh/m2 per year and a total suitable area of 73.75 km2. Macro cluster 2 comes third with a mean annual GHI of 2054.86 kWh/m2 per year and an area of 123.25 km2. The methodology used in this study is suitable for developing countries interested in incorporating renewable energy into their national energy mix whiles simultaneously planning for transmission network expansion.