The energy transition is progressing and Germany is leading the way in promoting renewable energies. An important measure to support this development has been the Renewable Energy Sources Act (EEG), which has made a decisive contribution to the spread of photovoltaic (PV) systems since its introduction in 2000. In 2023, significant changes were made to the EEG, particularly with regard to the feed-in tariff for PV systems.
Until the amendment of the EEG in 2023, there was a limit on the feed-in of active electricity at the grid connection point. This regulation stipulated that only a certain percentage of the installed capacity of a PV system could be fed into the public grid, with the exact limit varying between 50% and 70%. In some cases, this restriction meant that PV systems were unable to utilize their maximum energy production, resulting in a suboptimal use of green energy.
However, the 2023 amendment to the EEG abolished this regulation for new PV systems up to an output of 25 kWp and for existing systems up to 7 kWp. This change was a milestone for the industry and opened up new opportunities for PV system operators to increase their energy efficiency and maximize their contribution to the energy transition.
One innovative strategy that has emerged in connection with the 2023 amendment to the German Renewable Energy Sources Act (EEG) is the forecast-based charging (PBL) of PV systems. This method, also known as weather-based charging, aims to improve the efficiency and cost-effectiveness of PV systems by optimizing the use of the energy generated.
Predictive charging, also known as weather-based charging, is based on intelligent software that forecasts the energy production of the PV system and the household’s self-consumption. By integrating weather forecasts and historical data, the software makes it possible to make precise predictions about when the PV system is likely to reach its peak output and when self-consumption will be at its highest.
These forecasts enable the battery storage system to control charging in such a way that it is optimally tailored to the needs of the household. On sunny days, for example, charging is delayed in order to store the PV peaks and minimize feed-in to the public grid. This increases the self-consumption rate and boosts the profitability of the PV system.
| Time | Energy generation (kWh) | Consumption (kWh) | Battery charge (kWh) | Discharge (kWh) | Feed into the grid (kWh) |
|---|---|---|---|---|---|
| 08:00 | 8 | 4 | 0 | 0 | 4 |
| 10:00 | 16 | 6 | 2 | 0 | 8 |
| 12:00 | 20 | 10 | 10 | 0 | 0 |
| 14:00 | 15 | 12 | 3 | 0 | 0 |
| 16:00 | 10 | 15 | 0 | 5 | 0 |
| 18:00 | 10 | 7 | 0 | 3 | 0 |
This example calculation illustrates how the predicted charging can help to optimize the use of the PV energy generated and minimize the feed-in to the grid, which leads to a higher profitability of the PV system.
To prepare your business for the predicted charging with your PV system, you should consider the following steps:
If you require further information or would like support in implementing predicted charging in your company, we at Voltfang will be happy to help. Contact us for a no-obligation consultation and find out how you can get the most out of your PV system.
The amendment to the EEG in 2023 marked a turning point for the photovoltaic industry in Germany by opening up new opportunities to maximize the energy efficiency and profitability of PV systems. In particular, the predicted charging represents an innovative solution for overcoming the challenges of grid integration and taking an important step towards a sustainable energy future.
With the right use of technology and intelligent software, PV system operators can not only optimize their own electricity consumption, but also make an active contribution to stabilizing the power grid and increasing the use of renewable energy.
of renewable energies.
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