New yield study on roof-top PV systems for 2020 published

Distribution of the specific yield of roof-top PV systems 2020 in Germany
Distribution of the specific yield of roof-top PV systems 2020 in Germany

In the past year 2020, the yields of photovoltaic plants in Germany were above the long-term average, as in the previous years 2018 and 2019. According to the transmission system operators, photovoltaic systems generated 51.4 terawatt-hours of electrical energy in 2020, contributing 10.5 percent to the German electricity mix. With the other renewable energy systems - wind energy, bioenergy, and hydropower - the share of electrical energy generation was 50.6 percent; this was the first time that Germany's renewable energy systems generated more electricity than fossil-fuel power plants in a single calendar year.

The year 2020 was very high-yielding in all parts of Germany. Concerning the long-term average over the past nine years, yields in 2020 were on average 4.1 percent higher. In particular, the sunny spring from March to May with an extremely sunny April led to this above-average photovoltaic year. The figure shows the distribution of the specific yield of excellent photovoltaic roof systems for 2020 in Germany. Baden-Württemberg has the highest specific yields with values above 1150 kWh/kWp. In the south and east and the center of Germany, the photovoltaic roof systems record a specific yield of more than 1075 kWh/kWp. In the northwest, specific yields are somewhat lower but still above average.

Our study focused on rooftop photovoltaic systems with a nominal output of up to 30 kWp, as these systems account for around 90 percent of the photovoltaic systems installed in Germany, according to data from the German Federal Network Agency. These systems generally do not have a professional quality assurance and maintenance concept. Supervised remote monitoring systems are also not standard in this plant class, especially for rooftop plants up to 10 kWp.

The analysis's starting point is measurement data from photovoltaic plants that have an Internet-based remote monitoring system and whose data are publicly available. The raw data is first anonymized, not to conclude the individual plant or the operator. Subsequently, data processing and cleaning are performed by a two-stage algorithm in order to consider only photovoltaic plants without malfunctions. This ensures that the evaluated data results in yield values that reflect well-run and well-serviced photovoltaic systems.

Further information on the study, on research in the field of yield analysis of photovoltaic systems and contact details, can be found on our ↦ yield studies page.


Prof. Dr. Henrik te Heesen
Prof. Dr. Henrik te Heesen
Professor FB Umweltplanung/Umwelttechnik - FR Maschinenbau


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