Reeves D Cale, Haley Matthew, Uyanna Amara, Rai Varun
LBJ School of Public Affairs, The University of Texas at Austin, Austin TX, USA.
School of Public Policy, Georgia Institute of Technology, Atlanta GA, USA.
iScience. 2022 Jul 20;25(8):104794. doi: 10.1016/j.isci.2022.104794. eCollection 2022 Aug 19.
The rapid adoption of residential solar photovoltaic (PV) is recasting the role of individual households as a dynamic and potent construct critical for emissions mitigation and resilience of the electricity system. As residential PV enters more risk-averse customer segments, broader deployment of residential PV depends on overcoming both financial and informational barriers to adoption. Fast-changing residential PV technologies and associated policies means there is both lack of information and often misinformation among customers-gaps that are addressed effectively with local, trusted information networks, especially for big-ticket items such as residential PV. Here, we use an extensively validated agent-based model of residential PV adoption to analyze the effectiveness of different information intervention designs in spurring PV diffusion. We show that intervention designs are effective when they balance long-distance connections and local reinforcement, matching the intervention to both the informational needs of potential adopters and the structure of the underlying network.
住宅太阳能光伏（PV）的迅速采用正在重塑个体家庭的角色，使其成为电力系统减排和恢复力的关键、充满活力且强大的组成部分。随着住宅光伏进入风险规避性更强的客户群体，其更广泛的部署取决于克服采用过程中的财务和信息障碍。快速变化的住宅光伏技术及相关政策意味着客户中既存在信息匮乏，又常常存在错误信息——这些差距可通过本地、可信的信息网络有效解决，特别是对于住宅光伏这类高价商品。在此，我们使用经过广泛验证的基于主体的住宅光伏采用模型，来分析不同信息干预设计在推动光伏扩散方面的有效性。我们表明，当干预设计平衡长距离连接和本地强化，使干预与潜在采用者的信息需求以及基础网络结构相匹配时，这些干预设计是有效的。
