The Dynamic Energy Agents Model (DEAM) has been developed by Mark Barrett and Catalina Spataru and it models individual electricity consumers (domestic, non-domestic, transport) and supplier agents at half-hourly intervals for present and assumed future scenarios.

DEAM has been developed to investigate the energy demands and supplies of agents (households, businesses, generators, etc.) connected to a local electricity substation so as to calculate the possible future loads imposed on the substation. The model has been built for a representative set of data for Western Power Distribution. It calculates the energy flows for agents who are either domestic or non-domestic consumers, or for public energy suppliers.

DEAM produces primary results in half-hourly load curves which may be integrated to produce monthly or hourly results.  It produces sub-station load profiles up from individual premise level analysis; understand the potential for export in a locality; looking at various scenarios.

Model input data is produced by the AgentsDb database, which is a UK-wide non-domestic consumer database that uses HEED domestic data and applies it to any substation or area in the UK with Distribution Network Operator (DNO) data.

Both standard and stochastic versions of DEAM have been produced.

Please contact us if you have any question about DEAM.

Model summary

Type: Agent-based, bottom-up, techno-economic model
Purpose: Explore methods for coping with increased demand for electricity and to explore methods to manage new patterns of electricity demand and local generation
Policy impact A decision support tool, enabling DNOs to design their future network based on an accurate understanding of alternative costs and benefits
Spatial scale: Electricity substations in the UK, Distribution Network Operator (DNO)s
Temporal scale: Half-hourly
Main contacts: Catalina SpataruMark Barrett
Other contacts:  


Documentation is under development.


Conference Papers

Spataru, C. and Barrett, M. (2015) DEAM: A scalable Dynamic Energy model for demand and supply. IEEE UKSIM-AMSS 17th International Conference on Modelling and Simulation, 25-27 March 2015.


Barrett M., Spataru C. (2012) A Dynamic Energy Agents-Based Model (DEAM) - Falcon Project, November 2012. Report to the Energy Savings Trust.