(313g) Agent-Based Modelling of Peer-to-Peer Trading of Electricity with Heat Pump Integration in a Local Energy Market

The Paris Agreement and additional net-zero pledges hold nations around the globe accountable for their carbon footprint and urge them to explore new, eco-friendlier avenues in all fields of human activity. Electrification presents a very promising decarbonisation strategy with application in multiple domains and scales. It involves the substitution of fossil fuels with electricity produced from renewable sources to power processes and systems.

More specifically, to achieve decarbonisation targets via electrification, one approach is to increase the penetration of Distributed Energy Resources (DERs), that will be placed within the distributed electricity network. DERs are renewable sources of energy (photovoltaic panels, wind turbines) or energy storage (residential batteries, electric vehicles) that decentralise the wider energy generation system, facilitating the reduction of generation from fossil fuels while offering flexibility to their owners. Due to their potential dual role as energy consumers and producers residential DER owners are often referred to as prosumers. Given the additional stress that DER penetration can have on the distributed electricity network, the construction of Local Energy Markets (LEMs) for communities across the grid is a very promising strategy to manage potential issues. The electrification of heating and its resulting additional demand, encouraged in both the USA and Europe through grants for heat pump installations, will only accentuate the need to actively manage these networks, providing a strong incentive to explore the applicability of LEMs. LEMs are financial systems that support the exchange of electricity within a section of the distribution grid that may directly interact with the retail and wholesale power markets. Consequently, LEMs can be used to help balance such networks while providing prosumer benefit for the provision of flexibility.

In the current study, we build on the agent-based model of a LEM initially formulated by Hutty and Brown (Hutty & Brown, 2023) by introducing the heating requirements of market participants as an element to be modelled. This allows for the estimation of heating demands, which are then converted into electricity requirements and integrated into the overall household electricity demand. It is achieved through the appropriate manipulation of the thermodynamic equations that govern heat pump operation in order to ensure a constant house temperature of 18-20^oC. Moreover, variations in thermal insulation levels among houses are accounted for in the model development process. Consequently, the proposed LEM effectively regulates both the electricity and heating requirements of prosumers.

In summary, this work presents an optimized Local Energy Market (LEM) model designed to enhance market participation and real-life applicability. By extending coverage to a broader range of energy requirements, the proposed LEM can be a successful self-sufficient energy-financial system. The flexibility and autonomy the system offers to prosumers fosters sustainable energy practices among the general population and facilitates the integration of renewable resources into the electricity grid.

Acknowledgements

Funding from the UK Engineering and Physical Sciences Research Council (EPSRC) and EDF Energy R&D UK Centre Ltd (Grant Reference: EP/Y528808/1) are gratefully acknowledged.

Reference

Hutty, T. & Brown, S., 2023. An iterated double auction model for peer-to-peer electricity trading. Computer Aided Chemical Engineering, Volume 52, pp. 3141-3146.