Combining diverse data sources for CEDSS, an agent-based model of domestic energy demand

Nicholas Mark Gotts, Gary Polhill, Tony Craig, Carlos Galan-Diaz

Research output: Contribution to journalArticlepeer-review


CEDSS (Community Energy Demand Social Simulator) is an empirical agent-based model designed and built as part of a multi-method social science project investigating the determinants of domestic energy demand. Ideally, empirical modellers, within and beyond social simulation, would prefer to work from an integrated dataset, gatheredfor the purposes of developing the model. In practice, many have to work with less than ideal data, often including processed data from multiple sources external to the project. Moreover, what data will be required may not be clear at the start of the project. This paper describes the approach to dealing with these factors taken in developing CEDSS, and presents the completed model together with an outline of the calibration and validation procedure used. The discussion section draws together the most distinctive features of empirical data collection, processing and use for and in CEDSS, and argues that the approach taken is sufficiently robust to underpin the model?s purpose ? to generate scenarios of domestic energy demand to 2049.
Original languageEnglish
JournalStructure and Dynamics
Issue number1
Publication statusPublished - 1 Jan 2014


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