Abstract
Peer-to-peer energy trading—often implemented through virtual energy networks (VENs)—has expanded in Australia, the UK, the Netherlands, Germany, and Japan as rooftop solar adoption accelerates and retail customers seek greater control over their energy use. While P2P trading is frequently promoted as a way for households to arbitrage price gaps between retail prices and feed-in-tariffs, in high-solar contexts such as Australia it also has the potential to serve an important network function: absorbing excess daytime solar generation to reduce reverse power flows, voltage rise, and curtailment at the distribution level. We partner with an established VEN platform to group participating households into “virtual transformers,” each containing a mix of solar and non-solar homes.We randomize into treatment and control groups and virtual transformers. Treated clusters are assigned default trades in which solar producers sell to off-takers at a price between the retail rate and feed-in tariff, effectively splitting the gains from trade generated by that price gap. Control clusters remain in a baseline condition—active on the platform but not engaged in trading—before receiving the intervention at a later date. We also layer dynamic, event-day incentives onto the treated clusters by subsidizing daytime electricity to near zero on forecast high-solar days, enabling us to assess whether stronger, time-targeted incentives further increase local solar absorption and ease distribution-network constraints. Finally, we combine the experimentally estimated demand elasticities with engineering models of distribution networks to quantify how increased daytime load shifting would affect hosting capacity, reverse-flow frequency, and the long-run need for transformer and feeder upgrades.