Created by NOVELTIS for ECREEE during the ACP-EU project ECOWREX 2: Promoting Sustainable Energy Development through the use of Geospatial Technologies in West Africa This dataset shows the average Wind Speed at 80 meter high over the year 2013. The average is calculated from hourly time series data generated by NOVELTIS meso-scale Numeric Weather Prediction system. The resolution is 4km x 4km. The unit is m/s. Projection is latlon, EPSG 4326, WGS 84. This dataset is not indicated for local studies but only for regional comparison. The annual average was calculated from hourly time series data generated by NOVELTIS meso-scale Numeric Weather Prediction system over the full 2013 year. The values are calculated from NWP output extracted parameters: U = West-East component of the wind speed V = South-North component of the wind speed. The 2013 year was selected by NOVELTIS as TMY (typical meteorological year) through a regional climatic analysis for the period from 2000 to 2014. Minimum=2.893 m/s Maximum=6.664 m/s Mean=5.149 m/s StdDev=0.624 m/s

The suitability maps, contain information on locations suitable for installation of the respective wind electricity generation systems in accordance with the restrictive criteria adopted. Locations are evaluated according to their suitability for onshore wind systems deployment according to topographical, legal, and social constraints, and well as factors that could facilitate or impede wind generation development. The present study focus exclusively on land suitability for the installation of onshore wind turbine and wind farm. The study is conducted on a regional scale. The results can be used for identification of potential areas of interest for solar generation deployment, and as a support for integration between electricity grid expansion and off-grid electrification policies. Off-grid installations - practical scenario: Installation NOT connected to the electrical grid, ease of installation maximized

Created by NOVELTIS for ECREEE during the ACP-EU project ECOWREX 2: Promoting Sustainable Energy Development through the use of Geospatial Technologies in West Africa This dataset shows the average temperature at 2 meter over the year 2013. The average is calculated from hourly time series data generated by NOVELTIS meso-scale Numeric Weather Prediction system. The resolution is 4km x 4km. The unit is degree Celsius. Projection is latlon, EPSG 4326, WGS 84. This dataset is not indicated for local studies but only for regional comparison. The annual average was calculated from hourly time series data generated by NOVELTIS meso-scale Numeric Weather Prediction system over the full 2013 year. The parameter extracted from the NWP output is T2 = Temperature at 2 meter. The 2013 year was selected by NOVELTIS as TMY (typical meteorological year) through a regional climatic analysis for the period from 2000 to 2013. Minimum=22.163 °C Maximum=27.466 °C Mean=26.475 °C StdDev=0.641 °C

Dataset includes an estimation of the demand for electricity from households onto a geographic grid at 1km x 1km of spatial resolution. Dataset mainly focus on the demand for electricity of urban residential, commercial, and small industries, according to the WAPP 2013 (Miketa, A. and Merven, B., 2013) subdivision. Dataset does not include demand from heavy industry (e.g. mining), which connects to generation at a high voltage and generally requires less transmission and no distribution infrastructure. Taking that into consideration, in rural areas the electricity demand can be considered closely related to the number of inhabitants, the principal dis-aggregation algorithm, that estimates the electricity demand for each cell (x,y) of the geographic grid is based on:. Electricity demand(x,y) = electricity demand(capita) * number people(x,y) where Electricity demand(x,y) corresponds to the demand for the cell at the x,y position, the electricity demand per capita is calculated at national level according to IRENA 2013 data, and the number of people (x,y) corresponds to the people living in the cell at the x,y position Data is expressed as electricity demand in MWh per year per cell for the year 2015

Created by NOVELTIS for ECREEE during the ACP-EU project ECOWREX 2: Promoting Sustainable Energy Development through the use of Geospatial Technologies in West Africa This dataset shows the average Wind Power Density at 40 meter high over the year 2013. The average is calculated from hourly time series data generated by NOVELTIS meso-scale Numeric Weather Prediction system. The resolution is 4km x 4km. The unit is W/m2. Projection is latlon, EPSG 4326, WGS 84. This dataset is not indicated for local studies but only for regional comparison. The annual average was calculated from hourly time series data generated by NOVELTIS meso-scale Numeric Weather Prediction system over the full 2013 year. The values are calculated from NWP output extracted parameters: U = West-East component of the wind speed V = South-North component of the wind speed. ALT = inverse density AL = inverse perturbation density According to the following formula: WPD = 1/2* 1/(ALT+AL) * (WS)3 With WS = √(U2 + V2) The 2013 year was selected by NOVELTIS as TMY (typical meteorological year) through a regional climatic analysis for the period from 2000 to 2014. Minimum=27.706 W/m2 Maximum=583.235 W/m2 Mean=124.764 W/m2 StdDev=57.928 W/m2