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Energy transition
Nature Energy (2026)
When households install rooftop solar panels, they often increase their electricity consumption due to the perception of ‘free’ energy, a phenomenon known as the solar rebound effect. Energy scenarios should reflect this additional demand, while associated policy should incentivize use during sunny hours to limit system costs and unfair cost shifting.
Incorporating the solar rebound effect into official system planning may help ensure energy infrastructure is designed for realistic demand.
The solar rebound effect should not be treated as a fixed increase in demand, as its timing varies across hours and seasons and can substantially change infrastructure needs, system costs, and planning outcomes.
Tariffs and incentives that encourage rooftop solar PV households to shift flexible consumption to sunny hours can reduce system impacts, since rebound demand is least costly when it coincides with solar generation and more costly when it occurs in low-solar hours.
The solar rebound effect can shift system costs onto other electricity consumers without PV, creating regressive impacts as solar rollout increases, highlighting the need to quantify and monitor distributional effects.
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based on Delic, M. & Bucksteeg, M. Implications of the solar rebound effect for the European energy transition. Nat. Energy https://doi.org/10.1038/s41560-026-02031-8 (2026)
Rooftop photovoltaics (PV) are a cornerstone of Europe’s energy transition. However, their success may be undermined by the solar rebound effect (SRE), where PV owners may consume more electricity after installation because their solar power is essentially free to use. Current abatement scenarios and simulation studies fail to account for the additional electricity consumption induced by this effect, leaving an important blind spot in energy system planning. While empirical studies have repeatedly confirmed the SRE, robust evidence on its system-wide implications remains limited. Millions of households using rooftop solar may increase their electricity consumption, and depending on where the rebound effect occurs, this may trigger additional infrastructure investments and raise overall system costs. Such costs must be recovered through higher electricity tariffs, which raises distributional concerns given that solar households benefit while the costs are also borne by households that can’t afford PV.
Our analysis reveals that the SRE may increase electricity demand by 63–314 TWh by 2050, increasing Europe’s total demand by up to 5.1% in the worst-case scenario (Fig. 1c). Meeting this extra demand requires additional renewable generation and grid flexibility, increasing annual total power-system costs by €6.7–23.5 billion per year between 2030 and 2050 (up to 4.2% in 2050; Fig. 1d). If consumption rises mainly during sunny hours, the system can absorb increased demand at a lower cost. However, if rebound demand shifts into evenings and winter periods, it triggers higher needs for wind generation, batteries, and costly long-duration backup such as hydrogen, substantially increasing system costs and electricity prices. Finally, the SRE has a regressive impact, with system costs passed through to higher electricity prices that disproportionately affect non-PV adopters, unless current tariff structures are changed.
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a, PV generation profile (typical day) and schematic rebound demand profiles representing three rebound demand profiles: dynamic (time-shifted), simultaneous (coincident with PV generation), and sweeping (evenly distributed). b, Reference household electricity demand (typical weekday) and the corresponding load shapes under the same three rebound demand profiles. c, Total electricity demand (TWh yr−1) for the reference scenario and the maximum SRE case; coloured points indicate other SRE effect–strength/timing combinations; labels report the absolute value for the maximum SRE case and the percentage change relative to the reference. d, Annual total system costs (bn€ yr−1) for the reference scenario and the maximum SRE case; points and labels as in c. Figure adapted from Delic, M. & Bucksteeg, M. Nat. Energy https://doi.org/10.1038/s41560-026-02031-8 (2026).
We integrate empirically observed SRE intensities and profiles from scientific literature into an open-source energy system model covering power, heat, transport, and hydrogen sectors. The model chooses a least-cost mix of generation and storage to meet hourly demand while following a Paris Agreement-aligned path to climate neutrality by 2045. We simulate 34 European market areas from 2030 to 2050 in five-year steps and compare a baseline run without rebound to scenarios with low (7.7%), average (17.2%), and high (33%) rebound intensity. Because the timing of additional consumption is uncertain, we implement three different rebound demand profiles (see Fig. 1a, b): (simultaneous) concentrated around midday solar output, (sweeping) evenly distributed across the day, and (dynamic) capturing both immediate increases during sunny hours and systematic shifts of additional consumption into evening periods with seasonal variation.
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FernUniversität in Hagen, Hagen, Germany
Mensur Delic & Michael Bucksteeg
Institute of Energy Economics (EWI), University of Cologne, Cologne, Germany
Michael Bucksteeg
PubMed Google Scholar
PubMed Google Scholar
Correspondence to Mensur Delic.
The authors declare no competing interests.
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Delic, M., Bucksteeg, M. Why Europe’s solar rollout must account for the solar rebound effect. Nat Energy (2026). https://doi.org/10.1038/s41560-026-02026-5
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