TY - JOUR
T1 - Combining diverse data sources for CEDSS, an agent-based model of domestic energy demand
AU - Gotts, Nicholas Mark
AU - Polhill, Gary
AU - Craig, Tony
AU - Galan-Diaz, Carlos
N1 - Funding for the work reported was received from the European Commission under grant agreement SSH-CT-2008-225383 GILDED.
PY - 2014/1/1
Y1 - 2014/1/1
N2 - 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.
AB - 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.
M3 - Article
SN - 1554-3374
VL - 7
JO - Structure and Dynamics
JF - Structure and Dynamics
IS - 1
ER -