Impact of peer-to-peer trading and flexibility on local energy systems

Abstract

To meet the 2050 net zero emission targets, energy systems around the globe are being revisited to achieve multi-vector decarbonisation in terms of electricity, transport, heating and cooling. As energy systems become more decentralised and digitised, local energy systems will have greater potential to self-sustain and hence, decrease reliance on fossil-fuelled central generation. While the uptake of electric vehicles, heat pumps, solar and battery systems offer a solution, the increase in electricity demand poses challenges in terms of higher peak demand, imbalance and overloading. Additionally, the current energy market structure prevents these assets in the distribution network from reaching their true techno-economic potential in flexibility services and energy trading. Peer-to-peer energy trading and community-level control algorithms achieve better matching of local demand and supply through the use of transactive energy markets, load shifting and peak shaving techniques. Existing research addresses the challenges of local energy markets and others investigate the effect of increased distributed assets on the network. However, the combined techno-economic effect requires the co-simulation of both market and network levels, coupled with simultaneous system balance, cost and carbon intensity considerations.

Using bottom-up coordination and user-centric optimisation, this project investigated the potential of network-aware peer-to-peer trading and community-level control to increase self-sufficiency and self-consumption in energy communities. The techno-economic effects of these strategies are modelled while maintaining user comfort levels and healthy operation of the network and assets. The proposed strategies are evaluated according to their economic benefit, environmental impact and network stress. A case study in Scotland was employed to demonstrate the benefits of peer-to-peer trading and community self-consumption using future projections of demand, generation and storage. Additionally, the concept of energy smart contracts, embedded in blockchains, are proposed and demonstrated to overcome the major challenges of monitoring and contracting.

The results indicate benefits for various energy systems stakeholders. Distribution system end-users benefit from lower energy costs while system operators obtain better visibility of the local-level flexibility along with the associated technical challenges in terms of losses, imbalance and loading. From a commercial perspective, community energy companies may utilise this study to inform investment decisions regarding storage, distributed generation and transactive market solutions. Additionally, the insights about the energy smart contracts allow blockchain and relevant technology sectors to recognise the opportunities and challenges of smart contracts and distributed ledger technologies that are specific to the energy sector. On the broader scale, energy system operators, regulators and high-level decision-makers can compare the simulated impact of community-led energy transition on the net zero goals with large-scale top-down initiatives.