Optimal operation of an energy hub considering the uncertainty associated with the power consumption of plug-in hybrid electric vehicles using information gap decision theory

Moghaddas-Tafreshi, SM; Jafari, M; Mohseni, S; Kelly, S

Optimal operation of an energy hub considering the uncertainty associated with the power consumption of plug-in hybrid electric vehicles using information gap decision theory

Moghaddas-Tafreshi, SM Jafari, M Mohseni, S

Kelly, S

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Publication Type:: Journal Article
Citation:: International Journal of Electrical Power and Energy Systems, 2019, 112 pp. 92 - 108
Issue Date:: 2019-11-01

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Field	Value	Language
dc.contributor.author	Moghaddas-Tafreshi, SM	en_US
dc.contributor.author	Jafari, M	en_US
dc.contributor.author	Mohseni, S https://orcid.org/0000-0001-7367-3757	en_US
dc.contributor.author	Kelly, S https://orcid.org/0000-0002-8454-6144	en_US
dc.date.issued	2019-11-01	en_US
dc.identifier.citation	International Journal of Electrical Power and Energy Systems, 2019, 112 pp. 92 - 108	en_US
dc.identifier.issn	0142-0615	en_US
dc.identifier.uri	http://hdl.handle.net/10453/132920
dc.description.abstract	© 2019 Elsevier Ltd An energy hub is a multi-carrier energy system that is capable of coupling various energy networks. It increases the flexibility of energy management and creates opportunities to increase the efficiency and reliability of energy systems. When plug-in hybrid electric vehicles (PHEVs)are incorporated into the energy hub, batteries can act as an aggregated storage system, increasing the potential integration of variable renewable energy sources (RES)into power system networks. This paper presents a new model for the optimal operation of an energy hub that includes RES, PHEVs, fuel cell vehicles, a fuel cell, an electrolyzer, a hydrogen tank, a boiler, an inverter, a rectifier, and a heat storage system. A novel model is developed to estimate the uncertainty associated with the power consumption of PHEVs during trips using information gap decision theory (IGDT)under risk-averse and risk-seeking strategies. Simulation results demonstrate that the proposed method maximizes the objective function under the risk-neutral and risk-averse strategies, while minimizing the objective function under the risk-seeking strategy. Results from the modeling show that considering the uncertainty associated with the power consumption of PHEVs using IGDT enables the energy hub operator to make appropriate decisions when optimizing the operation of the energy hub against possible changes in power consumption of PHEVs.	en_US
dc.relation.ispartof	International Journal of Electrical Power and Energy Systems	en_US
dc.relation.isbasedon	10.1016/j.ijepes.2019.04.040	en_US
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.subject.classification	Energy	en_US
dc.title	Optimal operation of an energy hub considering the uncertainty associated with the power consumption of plug-in hybrid electric vehicles using information gap decision theory	en_US
dc.type	Journal Article
utslib.citation.volume	112	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/DVC (Research)
pubs.organisational-group	/University of Technology Sydney/DVC (Research)/Institute For Sustainable Futures
pubs.organisational-group	/University of Technology Sydney/Strength - ISF - Institute for Sustainable Futures
utslib.copyright.status	open_access	*
utslib.copyright.embargo	2021-11-01T00:00:00+1100
pubs.publication-status	Published	en_US
pubs.volume	112	en_US

Abstract:

© 2019 Elsevier Ltd An energy hub is a multi-carrier energy system that is capable of coupling various energy networks. It increases the flexibility of energy management and creates opportunities to increase the efficiency and reliability of energy systems. When plug-in hybrid electric vehicles (PHEVs)are incorporated into the energy hub, batteries can act as an aggregated storage system, increasing the potential integration of variable renewable energy sources (RES)into power system networks. This paper presents a new model for the optimal operation of an energy hub that includes RES, PHEVs, fuel cell vehicles, a fuel cell, an electrolyzer, a hydrogen tank, a boiler, an inverter, a rectifier, and a heat storage system. A novel model is developed to estimate the uncertainty associated with the power consumption of PHEVs during trips using information gap decision theory (IGDT)under risk-averse and risk-seeking strategies. Simulation results demonstrate that the proposed method maximizes the objective function under the risk-neutral and risk-averse strategies, while minimizing the objective function under the risk-seeking strategy. Results from the modeling show that considering the uncertainty associated with the power consumption of PHEVs using IGDT enables the energy hub operator to make appropriate decisions when optimizing the operation of the energy hub against possible changes in power consumption of PHEVs.

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http://hdl.handle.net/10453/132920