Abstract
Changing residential energy demand can play an essential role in transitioning to a green economy. Environmental psychology suggests that behavioral changes regarding energy use are affected by knowledge, awareness, motivation and social learning. Data on various behavioral drivers of change can explain energy use at the individual level, but it provides little information about implications for macro energy demand on regional or national levels. We address this challenge by presenting a theoretically-based and empirically-driven agent-based model to track aggregated impacts of behavioral changes among heterogeneous households. We focus on the representation of the multi-step changes in individual energy use behavior and on a quantitative assessment of their aggregated impacts on the regional level. We understand the behavioral complexity of household energy use as a dynamic process unfolding in stages, and explore the barriers for utilizing the full potential of a region for emissions reduction. We suggest a policy mix that facilitates mutual learning among consumers.
Original language | English |
---|---|
Pages (from-to) | 325–345 |
Number of pages | 21 |
Journal | Energy policy |
Volume | 118 |
DOIs | |
Publication status | Published - 1 Jul 2018 |
Keywords
- UT-Hybrid-D
- Residential energy
- Behavioral change
- Energy efficiency
- Agent-based modeling (ABM)