Expansion of PV for self-consumption reduces grid load

Fraunhofer Institute of Optronics, System Engineering and Image Evaluation – Applied System Technology (IOSB-AST) says Germany’s grid load is falling as more PV output is consumed on-site, but notes rising electrification in other sectors could reverse the trend.

Aug 12, 2025 - 21:30
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Expansion of PV for self-consumption reduces grid load

Fraunhofer Institute of Optronics, System Engineering and Image Evaluation – Applied System Technology (IOSB-AST) says Germany’s grid load is falling as more PV output is consumed on-site, but notes rising electrification in other sectors could reverse the trend.

From pv magazine Germany

Energy experts at Fraunhofer IOSB-AST analyzed load data from German distribution network operator Stadtwerke Erfurt (SWE Netz GmbH) over the past 14 years and found that higher self-consumption from photovoltaic systems has reduced grid loads.

They used publicly available data from the market master data register and found that the amount of energy supplied to end consumers in this grid area has declined steadily since 2010, according to Fraunhofer IOSB-AST.

“Our results show a strong correlation between declining grid load and the continuous expansion of photovoltaics in this grid area, especially since 2016,” said Tom Bender, project manager at Fraunhofer IOSB-AST.

However, experts expect a reversal in the coming years. Increasing electrification of mobility and heating, along with the expansion of power-to-gas applications, is expected to drive higher demand from the grid.

For medium-term planning, grid operators rely on regular forecasts of future grid load, the report said. Forecasts for the current and coming year are particularly important, as they form the basis for many energy-related decisions and processes. Inaccurate forecasts could pose significant economic risks.

According to IOSB-AST, the data sources now used enable far more precise modeling than the previous data model. A simulation for SWE Netz on a 15-minute basis for the reference year 2024 reduced the error in mapping the grid load from 3.89 GWh to 0.93 GWh, an improvement of 76%. The model accuracy was achieved by incorporating diurnal and seasonal patterns and long-term trends.

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