IRENA: Dataset With 10905 Sites for Solar PV Deployment Across Africa Totalling 4.9 TW

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IRENA said the research group that created the dataset defined the sites as model supply regions (MSRs). It said it used in-depth analysis of various existing datasets on resource potential, grid infrastructure, land use, and topography to create each MSR.

“This dataset fills an important research need by closing the gap between comprehensive datasets on African variable renewable electricity (VRE) potential on the one hand, and the input needed to run cost-optimization models on the other,” IRENA said. “It also allows a detailed analysis of the trade-offs involved in exploiting excellent, but far-from-grid resources as compared to mediocre but more accessible resources, which is a crucial component of power systems planning to be elaborated for many African countries.”

The model uses various parameters to select a geographically referenced subset of sites within each country. These include resource strength, population density, elevation, slope, land use, protected areas, and distance from roads.

The siting process defined the expected levelized cost of energy (LCOE) of each MSR by also including additional costs for substations, transmission lines, and road construction costs for grid connection.

“The MSRs were then ranked from lowest to highest expected LCOE,” IRENA said. “This allowed to screen out a high-ranking sub-selection of the MSRs in each country based on LCOE.”

The dataset offers 10,905 MSRs for solar PV across Africa with an estimated total capacity of 4.9 TW.

“It is seen that the most attractive locations (in LCOE terms) for solar PV plants tend to cluster near existing grid infrastructure, whereas the most attractive locations for wind power plants are spatially much more widely distributed,” the scientists said.

IRENA presented the dataset in “An all-Africa dataset of energy model ‘supply regions’ for solar photovoltaic and wind power,” which was recently published in Scientific Data.

“Several improvements to the dataset are under consideration for the future,” concluded IRENA.

Author: Emiliano Bellini

This article was originally published in pv magazine and is republished with permission.


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