Journal
ENVIRONMENTAL MODELLING & SOFTWARE
Volume 70, Issue -, Pages 163-177Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.envsoft.2015.04.014
Keywords
Agent-based modeling; Solar photovoltaic (PV); Complex systems; Technology adoption; Social networks; Bounded rationality
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Funding
- U.S. Department of Energy under its Solar Energy Evolution and Diffusion Studies (SEEDS) program within the SunShot Initiative [DE-EE0006129]
- Elspeth Rostow Memorial Fellowship
- Policy Research Institute (PRI) at the LBJ School of Public Affairs (UT Austin)
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Agent-based modeling (ABM) techniques for studying human-technical systems face two important challenges. First, agent behavioral rules are often ad hoc, making it difficult to assess the implications of these models within the larger theoretical context. Second, the lack of relevant empirical data precludes many models from being appropriately initialized and validated, limiting the value of such models for exploring emergent properties or for policy evaluation. To address these issues, in this paper we present a theoretically-based and empirically-driven agent-based model of technology adoption, with an application to residential solar photovoltaic (PV). Using household-level resolution for demographic, attitudinal, social network, and environmental variables, the integrated ABM framework we develop is applied to real-world data covering 2004-2013 for a residential solar PV program at the city scale. Two applications of the model focusing on rebate program design are also presented. (C) 2015 Elsevier Ltd. All rights reserved.
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