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Balancing potential of natural variability and extremes in photovoltaic and wind energy production for European countries

Abstract The increasing use of wind and solar power requires interventions to balance the associated variability in energy production. One option to reduce the costly interventions is to exploit the natural de-correlation of wind and irradiance. This study characterises the balancing potential of the natual variability in wind and photovoltaic energy production within and across eleven European countries. We use 20 years of highly resolved meteorological data from a post-processed regional reanalysis with a 6 km horizontal grid to calculate daily photovoltaic and wind power. Our results suggest a country-dependent reduction of the day-to-day variability in energy production by 29%–42% due to installing both PV and wind power capacities, compared to wind power only. The optimized photovoltaic to photovoltaic plus wind power generation ratios are 45–57% for maximizing balancing effects associated with the changing weather. We further identify on less than 10% of the days a simultaneous occurrence of extremes in photovoltaic and wind power across European countries. The cross-border balancing potentials for the extremes in renewable energy production are therefore high due to the spatio-temporal differences of the local weather.
- University of Cologne Germany
690, ddc:no
690, ddc:no
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).30 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
