Liu, F., Tait, S., Schellart, A. et al. (2 more authors) (2020) Reducing carbon emissions by integrating urban water systems and renewable energy sources at a community scale. Renewable and Sustainable Energy Reviews, 123. 109767. ISSN 1364-0321
Abstract
This paper presents a novel take on the energy-water nexus; exploring the coupling of renewable generation sources with drinking water distribution and wastewater collection assets that can store and release energy in response to temporal changes in residential heat demand. The paper presents the development of a simulation tool that uniquely integrates energy storage in drinking water reservoirs, heat recovery from sewers with wind turbine(s), solar photovoltaic panel(s) and a non-renewable source. Simulations at the scale of a 1000 household community and hourly intervals were used to ind the optimal energy generation mix that minimises the total annual carbon emissions (embedded and operational). Three different locations in the UK were studied. Results show that the integrated idealised system is able to satisfy the heat demand for up to 63% of the time across a year with no carbon emissions, and reduce the annual associated CO2 by 60% when compared to all heat demand being satisied by natural gas. This work shows that adopting such an interlinked system at a typical neighbourhood scale could help the UK meet its carbon emission obligations by substantially reducing the 18% of the UK’s CO2 emission (currently estimated to be) related to domestic heat use.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 Elsevier Ltd. |
Keywords: | Renewable energy; Optimisation; Service reservoir; Heat recovery; Residential heat demand; Carbon emission |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Civil and Structural Engineering (Sheffield) |
Funding Information: | Funder Grant number Engineering and Physical Sciences Research Council EP/N010124/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 08 Apr 2020 11:37 |
Last Modified: | 08 Apr 2020 11:37 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.rser.2020.109767 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:158449 |