Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
PIPENETa wireless sensor network for pipeline monitoring
Proceedings of the 6th international conference on Information processing in sensor networks
Decision support for sustainable option selection in integrated urban water management
Environmental Modelling & Software
NAWMS: nonintrusive autonomous water monitoring system
Proceedings of the 6th ACM conference on Embedded network sensor systems
The energy dashboard: improving the visibility of energy consumption at a campus-wide scale
Proceedings of the First ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings
The hitchhiker's guide to successful residential sensing deployments
Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems
Hot water DJ: saving energy by pre-mixing hot water
BuildSys '12 Proceedings of the Fourth ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings
WaterSense: water flow disaggregation using motion sensors
Proceedings of the Third ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings
FixtureFinder: discovering the existence of electrical and water fixtures
Proceedings of the 12th international conference on Information processing in sensor networks
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Water is a critical index of an organization's sustainability. Since water reuse consumes energy, water management requires careful analysis of energy implications. To this end, we study the energy-water nexus in a multi-building campus with a water delivery network that spans multiple grades (such as potable, reclaimed sewage, etc). Using data collected over several months, we answer these questions: (i) What are the trade-offs between the external water footprint of a campus and its internal energy footprint of water? (ii) Are improvements in either footprint realizable in practice? (iii) Does reducing the consumption of one water grade have more impact on the energy consumption than other water grades? (iv) Does rainwater harvesting help reduce a facility's energy footprint? We construct a multi-grade logical flow network with a per-link cost model for energy derived from the measured data. Under the constraint that demands are always met using the existing supplies, we optimize this flow-network for individually minimizing internal energy consumption of water and external water intake. Our study reveals the following: (i) minimizing external water footprint does not correspond to minimizing the internal energy footprint of water; (ii) demand reduction of different water grades impact the energy and water footprints differently; Contrary to intuition, reduction in second grade water demand yields highest reduction in water footprint while reduction in first grade water demand yields higher reduction in energy; (iii) Rainwater harvesting (RWH) can significantly reduce the energy footprint of a campus water network with sewage re-use. Our results show a potential for improving the operating condition of the campus's water network that can reduce the energy consumption by nearly 56 MWh (10.5%) and 99.6 MWh (18%) annually without and with RWH respectively.