Photovoltaic power potential in West Africa using long-term satellite data

Abstract

Abstract. This paper addresses long-term historical changes in solar irradiance in West Africa (3 to 20∘ N and 20∘ W to 16∘ E) and the implications for photovoltaic systems. Here, we use satellite irradiance (Surface Solar Radiation Data Set – Heliosat, Edition 2.1 – SARAH-2.1) and temperature data from a reanalysis (ERA5) to derive photovoltaic yields. Based on 35 years of data (1983–2017), the temporal and regional variability as well as long-term trends in global and direct horizontal irradiance are analyzed. Furthermore, a detailed time series analysis is undertaken at four locations. According to the high spatial resolution SARAH-2.1 data record (0.05∘×0.05∘), solar irradiance is largest (up to a 300 W m−2 daily average) in the Sahara and the Sahel zone with a positive trend (up to 5 W m−2 per decade) and a lower temporal variability (<75 W m−2 between 1983 and 2017 for daily averages). In contrast, the solar irradiance is lower in southern West Africa (between 200 W m−2 and 250 W m−2) with a negative trend (up to −5 W m−2 per decade) and a higher temporal variability (up to 150 W m−2). The positive trend in the north is mostly connected to the dry season, whereas the negative trend in the south occurs during the wet season. Both trends show 95 % significance. Photovoltaic (PV) yields show a strong meridional gradient with the lowest values of around 4 kWh kWp−1 in southern West Africa and values of more than 5.5 kWh kWp−1 in the Sahara and Sahel zone.

Convection‐Permitting ICON‐LAM Simulations for Renewable Energy Potential Estimates Over Southern Africa

“…In Neher et al. (2020) the SARAH‐2 satellite data product with 30‐min temporal and 0.05° spatial resolution was used to derive the solar energy potential for West Africa. Nevertheless, satellite‐derived products face shared challenges due to observation gaps in space and time caused by satellite routines, atmospheric noise from clouds and aerosols, and the need for accurate retrieval algorithms (Huang et al., 2019; Weissman et al., 2012).…”

“…For example, Elsner (2019) provided off-shore wind energy potential estimates for the African coastal areas by using the satellite-based Blended Sea Winds data set with spatial resolution of 0.25°and temporal resolution of 6-hourly. In Neher et al (2020) the SARAH-2 satellite data product with 30-min temporal and 0.05°spatial resolution was used to derive the solar energy potential for West Africa. Nevertheless, satellite-derived products face shared challenges due to observation gaps in space and time caused by satellite routines, atmospheric noise from clouds and aerosols, and the need for accurate retrieval algorithms (Huang et al, 2019;Weissman et al, 2012).…”