Anticipating distributional impacts of peer-to-peer energy trading: Inference from a realist review of evidence on Airbnb
Researcher Mike Fell, from UCL Energy Institute talks about peer-to-peer (P2P) trading systems by assessing and learning from the impact of AirBnB.
There are plenty of services aspiring to be the Airbnb of energy. These peer-to-peer (P2P) schemes let people buy and sell electricity directly between each other. For example, if I had a solar panel and was in the same scheme as you, you could buy my excess generation. Similar drivers exist in energy as for accommodation, with the promise of savings for buyers, better income for sellers, and potentially a more personal experience.
But while disruptive new services like Airbnb or its equivalents in energy hold many benefits, they also pose challenges. In the case of Airbnb, we’ve probably all heard about its potential to drive up rents and displace local people.
But the world has had more than a decade, and millions of stays, to learn about the impacts of Airbnb. In energy, all we have is a relative handful of small scale trials, often with small numbers of participants. This means that policymakers, regulators, and service designers are potentially flying blind when it comes to anticipating the impacts of the emergence of P2P-like arrangements in energy.
Peer-to-peer (P2P) energy trading – where energy prosumers transact directly between each other – could help enable transition to a low-carbon energy system. If it is to be supported in policy and regulation, it is important to anticipate the distributional impacts (or how it might impact segments of society differently). However, real-world evidence on P2P energy trading is currently extremely limited. To address this challenge in the short- to medium-term, this study aimed to explore what might be learned from the extensive body of research on a comparable offering in the accommodation sector: Airbnb.