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Agent-based modeling of energy technology adoption: Empirical integration of social, behavioral, economic, and environmental factors

机译:基于代理的能源技术采用建模:社会,行为,经济和环境因素的经验整合

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摘要

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.
机译:用于研究人类技术系统的基于代理的建模(ABM)技术面临两个重要挑战。首先,代理人的行为规则通常是临时性的,因此很难在较大的理论范围内评估这些模型的含义。其次,由于缺乏相关的经验数据,许多模型无法得到适当的初始化和验证,从而限制了此类模型在探索紧急属性或政策评估方面的价值。为了解决这些问题,在本文中,我们提出了一种基于理论和经验驱动的基于代理的技术采用模型,并将其应用于住宅太阳能光伏(PV)。使用针对人口,态度,社会网络和环境变量的家庭级分辨率,我们开发的集成ABM框架被应用于涵盖2004-2013年城市规模住宅太阳能光伏计划的真实数据。还介绍了该模型的两个应用程序,重点是折扣程序设计。 (C)2015 Elsevier Ltd.保留所有权利。

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