An agent-based spatiotemporal integrated approach to simulating in-home water and related energy use behaviour: A test case of Beijing, China
An agent-based spatiotemporal integrated approach to simulating in-home water and related energy use behaviour: A test case of Beijing, China
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基于主体的时空综合方法来模拟家庭用水和相关能源使用行为：中国北京的测试案例
DOI：
10.1016/j.scitotenv.2019.135086
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发表时间：
2020
影响因子：
9.8
通讯作者：
Yi Liu
中科院分区：
文献类型：
--
作者：
Chengxiang Zhuge;Min Yu;Chunyan Wang;Yilan Cui;Yi Liu
住宅部门的水和能源消耗高度相关。更好地了解这种相互关系将有助于通过技术创新、管理和政策等方式节约用水和能源。最近，在水-能源需求分析和建模方面越来越需要更高的时空分辨率，因为其结果将对水和能源系统的政策分析和基础设施规划更加有用。作为回应，本文开发了一种基于Agent的时空集成方法来模拟每个家庭或个人Agent在一整天中以秒为单位的水能源消耗，考虑了户外活动的影响（例如，工作和购物）的家庭活动（例如，洗澡、做饭和清洁）。综合办法在中国首都北京进行了试验。结果表明，24小时水耗与能耗的分布规律基本一致，水耗与能耗之间具有高度的相关性（Pearson相关系数为0.89）;空间分析结果表明，居住在中心城区和外围城区中心城区的居民用水和相关能源消耗量较大，水与能量的相关性也随空间而变化。这样的空间和时间上明确的结果预期对政策制定有用（例如，分时电价）以及水和能源部门的基础设施规划和优化。
Water and energy consumptions in the residential sector are highly correlated. A better understanding of the correlation would help save both water and energy, for example, through technological innovations, management and policies. Recently, there is an increasing need for a higher spatiotemporal resolution in the analysis and modelling of water-energy demand, as the results would be more useful for policy analysis and infrastructure planning in both water and energy systems. In response, this paper developed an agent-based spatiotemporal integrated approach to simulate the water-energy consumption of each household or person agent in second throughout a whole day, considering the influences of out-of-home activities (e.g., work and shopping) on in-home activities (e.g., bathing, cooking and cleaning). The integrated approach was tested in the capital of China, Beijing. The temporal results suggested that the 24-hour distributions of water and related energy consumptions were quite similar, and the water-energy consumptions were highly correlated (with a Pearson correlation coefficient of 0.89); The spatial results suggested that people living in the central districts and the central areas of the outer districts tended to consume more water and related energy, and also the water-energy correlation varies across space. Such spatially and temporally explicit results are expected to be useful for policy making (e.g., time-of-use tariffs) and infrastructure planning and optimization in both water and energy sectors.