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  • Combined wind-solar electri...
    Jánosi, Imre M.; Medjdoub, Karim; Vincze, Miklós

    Renewable & sustainable energy reviews, November 2021, 2021-11-00, Letnik: 151
    Journal Article

    In this work we analyze wind speed and solar irradiation data of high spatial and temporal res-olution for an extended area of north-western Africa including the Mediterranean Sea. We ex-ploit the ERA5 data bank compiled and maintained by the European Centre for Medium Range Weather Forecast (ECMWF). One of the new products they provide is horizontal wind speed components at a height of 100 m (modern wind turbines have a hub height between 80 and 120 m). We demonstrate that the desert area is an optimal location for wind- and solar electricity production for two peculiar aspects. Firstly, the wind speeds at 100 m over the Sahara are al-most as large as wind speeds over the open sea. Wind speed differences between the standard 10 m altitude and 100 m level are considerably larger over the desert area than over the sea. Secondly, there are utilizable anti-correlations between local wind speeds at 100 m and surface solar radiations over the Sahara. As far as we know, such anti-correlations over our target area are not considered until very recently as an exploitable source of combined solar-wind electricity production. We provide a theoretically optimum combination of the two resources in a simple model framework. The result is that resource combinations between 60-40% and 70-30% wind-solar electricity aggregation (depending on the geographic location) provide and optimally smooth output with a minimal loss of total production achieved by either pure wind or pure photo-voltaic generation. •Wind speeds at 100 m height over the Sahara are as strong as over open sea.•Spatial correlation lengths for the wind fields are extremely large.•Saharan wind regularly intensifies during nighttime periods, in each season.•Anti-correlations between integrated solar and wind resources improve the smoothness.•The total output power loss at an optimal resource combination is low.