Abstract
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.
Original language | English |
---|---|
Article number | 135086 |
Number of pages | 12 |
Journal | Science of the Total Environment |
Volume | 708 |
Early online date | 22 Nov 2019 |
DOIs | |
Publication status | Published - 15 Mar 2020 |
Keywords
- Activity-based modelling
- Agent-based modelling
- CONSERVATION
- CONSUMPTION
- Consumption behaviour
- DEMAND MANAGEMENT
- DOMESTIC ENERGY
- EFFICIENCY
- END-USE
- FRAMEWORK
- House appliances
- NEXUS
- Nexus of water and energy
- RESIDENTIAL WATER
- TECHNOLOGY ADOPTION