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Multilayer Agent-Based Modeling and Social Network Framework to Evaluate Energy Feedback Methods for Groups of Buildings

机译:基于多层Agent的建模和社交网络框架,用于评估建筑群的能量反馈方法

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Important energy reductions can be achieved in the building sector by providing occupants with feedback about their energy-consumption levels. Recent studies link the success of energy-feedback methods to the level of occupant engagement with people in their social circles and the resulting peer pressure to conform to certain social norms. Despite promising results, the literature remains limited in scope to individual rather than groups of buildings. This has limited the design of feedback initiatives leveraging social connections that exist, or that can be induced, within and between buildings. The current paper addresses the identified gap by proposing a multilayer agent-based model that serves as a test bed to simulate and optimize feedback methods applied on any building stock (e.g.,community and city). Monte Carlo and sensitivity analyses show that connecting occupants of different buildings, while increasing their engagement with the feedback mechanism, can lead to energy reductions exceeding 10%. The findings confirm the role of social networks in energy-conservation diffusion, setting the stage for large-scale and socially engaging energy-conservation initiatives. (C) 2017 American Society of Civil Engineers.
机译:通过向居住者提供有关其能耗水平的反馈,可以在建筑领域实现重要的节能减排。最近的研究将能量反馈方法的成功与乘员在社交圈中与人们的参与程度以及由此产生的要求遵守某些社会规范的同伴压力联系起来。尽管取得了令人鼓舞的结果,但文献的范围仍然局限于单个建筑物而不是建筑物组。这限制了利用建筑物内部和建筑物之间存在或可以诱发的社会联系的反馈计划的设计。当前的论文通过提出一种基于多层代理的模型来解决已发现的空白,该模型可以用作模拟和优化适用于任何建筑群(例如社区和城市)的反馈方法的测试平台。蒙特卡洛(Monte Carlo)和敏感性分析表明,连接不同建筑物的居住者在增加他们与反馈机制的互动的同时,可以减少超过10%的能源。这些发现证实了社会网络在节能推广中的作用,为大规模和社会参与的节能举措奠定了基础。 (C)2017年美国土木工程师学会。

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