Residential load management in an energy hub with heat pump water heater

Setlhaolo, D; Sichilalu, S; Zhang, J

Residential load management in an energy hub with heat pump water heater

Setlhaolo, D Sichilalu, S Zhang, J

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Publication Type:: Journal Article
Citation:: Applied Energy, 2017, 208 pp. 551 - 560
Issue Date:: 2017-12-15

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Field	Value	Language
dc.contributor.author	Setlhaolo, D	en_US
dc.contributor.author	Sichilalu, S	en_US
dc.contributor.author	Zhang, J https://orcid.org/0000-0003-2616-6722	en_US
dc.date.available	2020-05-25T19:04:19Z
dc.date.issued	2017-12-15	en_US
dc.identifier.citation	Applied Energy, 2017, 208 pp. 551 - 560	en_US
dc.identifier.issn	0306-2619	en_US
dc.identifier.uri	http://hdl.handle.net/10453/125349
dc.description.abstract	© 2017 Elsevier Ltd Today, as a consequence of the growing installation of efficient technologies, such as combined heat and power (CHP) as a co-generation, the integration of electricity through grid supply, Photovoltaic (PV) and energy storage systems as an integrated network is attracting a lot of attention in smart grid applications. To model the interaction among electricity and natural gas, the energy hub framework is adopted to determine a modelling procedure for such multi-carrier energy systems. This paper presents a residential energy hub model for a smart home as a modified framework of conventional energy hubs in a smart grid with consideration of heat pump water heater, coordination of sources and carbon emissions. Therefore, this study is twofold; the first part optimizes the operation of the combined CHP, Photovoltaic and storage system under dynamic pricing. Since residential load management plays a key role in realizing household demand response programs in a smart grid, performing optimal load management in the proposed residential energy hub model is also studied in this paper. To achieve this, the optimization problem is extended by considering modelling of a heat pump water heater. It is also found out that CO2 signal could give customers an environmental motivation to shift or reduce loads during peak hours, as it would enable co-optimization of electricity consumption costs and carbon emissions reductions.	en_US
dc.relation.ispartof	Applied Energy	en_US
dc.relation.isbasedon	10.1016/j.apenergy.2017.09.099	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.subject.classification	Energy	en_US
dc.title	Residential load management in an energy hub with heat pump water heater	en_US
dc.type	Journal Article
utslib.citation.volume	208	en_US
utslib.for	0915 Interdisciplinary Engineering	en_US
utslib.for	09 Engineering	en_US
utslib.for	14 Economics	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	open_access	*
pubs.publication-status	Published	en_US
pubs.volume	208	en_US

Abstract:

© 2017 Elsevier Ltd Today, as a consequence of the growing installation of efficient technologies, such as combined heat and power (CHP) as a co-generation, the integration of electricity through grid supply, Photovoltaic (PV) and energy storage systems as an integrated network is attracting a lot of attention in smart grid applications. To model the interaction among electricity and natural gas, the energy hub framework is adopted to determine a modelling procedure for such multi-carrier energy systems. This paper presents a residential energy hub model for a smart home as a modified framework of conventional energy hubs in a smart grid with consideration of heat pump water heater, coordination of sources and carbon emissions. Therefore, this study is twofold; the first part optimizes the operation of the combined CHP, Photovoltaic and storage system under dynamic pricing. Since residential load management plays a key role in realizing household demand response programs in a smart grid, performing optimal load management in the proposed residential energy hub model is also studied in this paper. To achieve this, the optimization problem is extended by considering modelling of a heat pump water heater. It is also found out that CO2 signal could give customers an environmental motivation to shift or reduce loads during peak hours, as it would enable co-optimization of electricity consumption costs and carbon emissions reductions.

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http://hdl.handle.net/10453/125349