A two-stage multi-objective stochastic optimization strategy to minimize cost for electric bus depot operators

Rafique, S; Nizami, MSH; Irshad, UB; Hossain, MJ; Mukhopadhyay, SC

A two-stage multi-objective stochastic optimization strategy to minimize cost for electric bus depot operators

Rafique, S Nizami, MSH Irshad, UB Hossain, MJ Mukhopadhyay, SC

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Publisher:: ELSEVIER SCI LTD
Publication Type:: Journal Article
Citation:: Journal of Cleaner Production, 2022, 332
Issue Date:: 2022-01-15

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Field	Value	Language
dc.contributor.author	Rafique, S
dc.contributor.author	Nizami, MSH
dc.contributor.author	Irshad, UB
dc.contributor.author	Hossain, MJ
dc.contributor.author	Mukhopadhyay, SC
dc.date.accessioned	2023-03-19T23:46:27Z
dc.date.available	2023-03-19T23:46:27Z
dc.date.issued	2022-01-15
dc.identifier.citation	Journal of Cleaner Production, 2022, 332
dc.identifier.issn	0959-6526
dc.identifier.issn	1879-1786
dc.identifier.uri	http://hdl.handle.net/10453/167630
dc.description.abstract	The electrification of large-scale bus depots will bring challenges for bus depot operators (BDOs) aiming to minimize operational costs. A potential solution for BDOs managing electric buses (EBs) with large batteries that are capable of vehicle-to-grid (V2G) operational functionalities, along with on-site generation facilities, is to actively participate in the energy market. This paper proposed a novel two-stage multi-objective stochastic optimization-based energy management system (EMS) for BDOs to trade energy in a day-ahead (DA) energy market while considering the expected cost of energy imbalances in the real-time (RT) market. The optimization model for charge–discharge scheduling is based on a mixed-integer linear programming approach. The uncertainties associated with the DA forecast are complemented by a stochastic model. Minimizing the cost of electricity and the penalty costs for battery capacity degradation are the objectives that need to be met simultaneously. The proposed EMS is evaluated using simulation studies considering a hypothetical bus depot in Australia. The effectiveness of the proposed EMS for overall financial savings is validated by comparing its performance with state-of-the-art scheduling strategies. Results show that the net energy cost for the proposed EMS is 38% lower compared to a deterministic scheduling strategy that does not allow V2G flexibilities, 33% lower compared to a deterministic scheduling strategy that allows V2G flexibilities and 17% lower compared to a stochastic scheduling strategy that minimizes overall costs.
dc.language	English
dc.publisher	ELSEVIER SCI LTD
dc.relation.ispartof	Journal of Cleaner Production
dc.relation.isbasedon	10.1016/j.jclepro.2021.129856
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0907 Environmental Engineering, 0910 Manufacturing Engineering, 0915 Interdisciplinary Engineering
dc.subject.classification	Environmental Sciences
dc.title	A two-stage multi-objective stochastic optimization strategy to minimize cost for electric bus depot operators
dc.type	Journal Article
utslib.citation.volume	332
utslib.for	0907 Environmental Engineering
utslib.for	0910 Manufacturing Engineering
utslib.for	0915 Interdisciplinary Engineering
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	closed_access	*
dc.date.updated	2023-03-19T23:46:26Z
pubs.publication-status	Published
pubs.volume	332

Abstract:

The electrification of large-scale bus depots will bring challenges for bus depot operators (BDOs) aiming to minimize operational costs. A potential solution for BDOs managing electric buses (EBs) with large batteries that are capable of vehicle-to-grid (V2G) operational functionalities, along with on-site generation facilities, is to actively participate in the energy market. This paper proposed a novel two-stage multi-objective stochastic optimization-based energy management system (EMS) for BDOs to trade energy in a day-ahead (DA) energy market while considering the expected cost of energy imbalances in the real-time (RT) market. The optimization model for charge–discharge scheduling is based on a mixed-integer linear programming approach. The uncertainties associated with the DA forecast are complemented by a stochastic model. Minimizing the cost of electricity and the penalty costs for battery capacity degradation are the objectives that need to be met simultaneously. The proposed EMS is evaluated using simulation studies considering a hypothetical bus depot in Australia. The effectiveness of the proposed EMS for overall financial savings is validated by comparing its performance with state-of-the-art scheduling strategies. Results show that the net energy cost for the proposed EMS is 38% lower compared to a deterministic scheduling strategy that does not allow V2G flexibilities, 33% lower compared to a deterministic scheduling strategy that allows V2G flexibilities and 17% lower compared to a stochastic scheduling strategy that minimizes overall costs.

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http://hdl.handle.net/10453/167630