Modeling the adoption of building efficiency technologies: A review of methods and datasets
Forecasts of the national energy and CO2 emissions reductions potential of building energy efficiency technologies depend on the assumed rates at which the technologies diffuse into targeted segments of building energy use. These rates stem on the one hand from technology stock-and-flow dynamics – rates of new construction, retrofits, and replacement, for example – and on the other hand from the behavioral dynamics of consumer or organization technology adoption decisions. While stock-and-flow models are a growing area for buildings research, less is known about building technology adoption models and their application to forecasts of future building energy use. This paper provides a summary of potential methods for quantitatively representing building technology adoption behavior as part of national or regionallevel energy use forecasts. A range of model types are covered that vary in complexity and data requirements, and recent examples of their use as part of energy and CO2 projections are briefly discussed. The paper then identifies and prioritizes the datasets available to support such models. Based on this review of models and datasets, the paper assesses the state of the art in building technology adoption modeling and suggests areas for further research.