Solar panels influence neighbors’ energy choices, Swiss study finds

A single solar roof can influence more than the household beneath it. In a simulation based on Swiss data, installing one additional residential solar photovoltaic system generated a median 0.07 additional solar PV systems, 0.05 additional electric vehicles and 3.7 MWh of annual electricity savings through the behavior of nearby households.

Benedikt Janzen of Germany’s University of Passau and Patrick Bigler of Switzerland’s University of Lausanne reached that estimate by studying geocoded data from 260,000 households in the canton of Bern, observed between 2008 and 2019. Their analysis combined electricity consumption, solar PV and electric vehicle ownership with household characteristics and the distance to nearby solar installations.

The closer the installation, the stronger the measured association. Each additional solar array within 100 meters corresponded to a 0.21% reduction in annual electricity consumption, or around 11 kWh. An array within 10 meters corresponded to a 2.1% reduction. The researchers also found that a nearby installation increased the probability of solar adoption by 0.02 percentage point and electric vehicle adoption by 0.01 percentage point at 100 meters.

Those percentages are small in absolute terms, but the researchers compared them with baseline adoption probabilities of 1% for solar PV and 0.44% for EVs. At 100 meters, they described the relative increases as 2% for solar adoption and 2.3% for EV adoption; within 10 meters, the increases were 20% and 23%, respectively. The study documents a geographic spillover, but Janzen and Bigler say its magnitude and nature will depend on local context.

What does that change, concretely? A subsidy or information campaign aimed at one household may have benefits beyond that address if neighbors copy what they see or discuss. The researchers suggest highlighting solar adoption within neighborhoods and connecting prospective adopters with households that already have PV. Their result gives policymakers a reason to count those local effects alongside the direct benefits of each installation.