An Empirically Grounded Model of Green Electricity Adoption in Germany: Calibration, Validation and Insights into Patterns of Diffusion

Authored by Friedrich Krebs

Date Published: 2017

DOI: 10.18564/jasss.3429

Sponsors: German Federal Ministry of Education and Research (BMBF)

Platforms: No platforms listed

Model Documentation: ODD Flow charts Pseudocode

Model Code URLs: Model code not found

Abstract

Spatially explicit agent-based models ( ABM) of innovation diffusion have experienced growing attention over the last few years. The ABM presented in this paper investigates the adoption of green electricity tariffs by German households. The model represents empirically characterised household types as agent types which differ in their decision preferences regarding green electricity and other psychological properties. Agent populations are initialised based on spatially explicit socio demographic data describing the sociological lifestyles found in Germany. For model calibration and validation we use historical data on the German green electricity market including a rich dataset of spatially explicit customer data of one of the major providers of green electricity. In order to assess the similarity of the simulation results to historical observations we introduce two validation measures which capture different aspects of the green electricity diffusion. One measure is based on the residuals of spatially-aggregated time series of model indicators and the other measure considers a temporally aggregated but spatially disaggregated indicator of spatial spread. Finally, we demonstrate the descriptive richness of the model by investigating simulation outputs of the calibrated model in more detail. In particular, the results provide insights into the dynamics of the spatial and lifestyle heterogeneity ``underneath{''} the diffusion curve of green electricity in Germany.

Tags

Simulation Agent-based models behavior Innovation Diffusion systems Innovations Protocol Green electricity Spatially explicit agent-based model Empirical calibration and validation