- University of Sheffield researchers have developed a simulation to show how peer-to-peer energy trading (P2P) - where neighbours can buy and sell energy with each other - could work and the impact this might have on bills and carbon emissions
- Study simulated a neighbourhood with 25 houses each equipped with various energy sources and consumers and used real time data on electricity demand
- Households quickly learned to buy and sell electricity with each other, but took longer to figure out how to trade heat.
- Simulation shows households saved an average of £19.59 per week when trading electricity and heat in winter and £16.69 per week in spring
In the study, published in the journal Applied Energy, researchers developed a computer simulation to predict how energy trading between neighbours could work and the impact this could have on their bills, the national grid and carbon emissions.
The research simulated a neighbourhood with 25 houses, each equipped with various energy sources, such as solar panels and heat pumps. Each home had an electric vehicle and was connected to a shared electrical grid and small heat network with the rest of the neighbourhood.
Different scenarios were modelled, which included households trading only electricity or both electricity and heat.
To make the simulation realistic, real-world data was harnessed for weather, electricity demand and car usage. The efficiency of heat pumps, the capacity of batteries and the performance of solar panels were also considered. The simulation was run over two different weeks - one in spring and the other in winter - to see how energy trading between homes might work.
Results show that neighbours quickly learned to buy and sell electricity with each other, but took longer to figure out how to trade heat. The price of electricity fluctuated but remained relatively stable.
In winter, households saved an average of £9.52 per week on their energy bills when they could trade electricity only and £19.59 per week when they could trade both electricity and heat. In spring, the average saving was £16.99 per week from trading electricity alone and £16.69 from trading electricity and heat.
Furthermore, trading energy with neighbours lowered the demand on the main power grid, including during peak times, resulting in less grid strain in both winter and spring. Electric vehicles charged more during sunny periods and heat pumps were operated more efficiently when both electricity and heat could be traded.
Professor Sol Brown, Professor of Process and Energy Systems at the University of Sheffield, who led the study, said: “When most people boil the kettle at home, switch on their heating or decide to do the washing, they know they are getting the energy for this from their energy company at a price set by their tariff. But what if we had a different system which also gave people the option to buy energy from their neighbours, who might be selling it at a reduced rate because they are not using as much energy at that particular time of day?
“Our research ran a simulation of this and found that peer-to-peer energy trading worked well between neighbours, saved them money on their energy bills, reduced carbon emissions and strain on the UK’s national grid. We also feel this could encourage households to adopt more green energy technologies, such as solar panels, energy storage systems and electric vehicles, as the system gives people more options regarding the energy they use, how much it costs and also when they can sell their own energy to neighbours at quieter times in their daily routine.”
Professor Brown added: “Many countries’ market regulations, including here in the UK, don’t yet support peer to peer energy trading, but interest is growing and some energy companies have been testing the systems in recent years. We hope that our research can support this exploration by demonstrating how the system could work and the impact it could have on energy prices and the environment.”
The study, P2P trading of heat and power via a continuous double auction, is published in the journal Applied Energy. To read the paper, visit: https://doi.org/10.1016/j.apenergy.2024.123556