Integrated Assessment Models (IAMs) like MESSAGE have been widely used as key instruments to develop long-term energy and emission scenarios and to identify cost-effective patterns of resource use and technology deployment over time, particularly in the context of climate change mitigation.
Yet, one of the major deficiencies of most current models is their limited representation of heterogeneity and consumer behavior on the demand side of the energy system. Behavior cannot be ignored, however, when it comes to system-wide modeling, as it is a critical aspect of policy and decision making. The objective of this project is to develop a bridging approach between detailed vehicle-choice models and more aggregated global IAM frameworks. More specifically, the MESSAGE approach disaggregates light-duty vehicle demands into a mix of consumer groups and then assigns additional cost terms (“disutility costs”) to the vehicle technologies within each of these groups, in order to capture non-cost barriers to alternative fuel vehicle adoption.
In one formulation, for instance, consumers are divided up along three separate dimensions, each with three distinct consumer types (for a total of 27 groups):
Region-specific disutility costs are estimated using the MA3T vehicle-choice model of Oak Ridge National Laboratory. The ultimate goal of the improved behavioral modeling framework is to generate scenarios that are more policy-relevant.
Last edited: 28 April 2015
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