Optimal Scheduling Model for Renewable Energy Source-Assisted Electric and Hydrogen Vehicle Charging Station in HPS Market

Hyeon Woo; Yongju Son; Sungyun Choi

doi:10.1109/PESGM52003.2023.10252498

Optimal Scheduling Model for Renewable Energy Source-Assisted Electric and Hydrogen Vehicle Charging Station in HPS Market

Hyeon Woo^*
, Yongju Son
, Sungyun Choi

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Citations (Scopus)

Abstract

As eco-friendly vehicles, such as electric vehicles (EVs) and hydrogen vehicles (HVs), become more popular, the heavy charging loads due to EV charging stations (EVCSs) and HV charging stations (HVCSs) cause additional challenges in the main grid. In response, the idea of renewable energy source-assisted charging stations, which can be used as cost-effective EV and HV charging stations (EHVCSs), has attracted attention. This paper proposes a framework for the stochastic optimal operation of EHVCSs to reduce the amount of power they need to purchase from the main grid and to maximize their revenues through means such as charging fees and hydrogen energy portfolio standard (HPS) sales. To enhance the profitability of HEVCS, the EHVCS can sell hydrogen into the HPS market by generating power through fuel cells installed in HVCSs. The optimization problem is formulated as a nonlinear programming problem given the nature of AC power flow constraints, which is non-convex. Therefore, the problem is transformed into a convex problem by convexifying the problem using second-order conic programming relaxation.

Original language	English
Title of host publication	2023 IEEE Power and Energy Society General Meeting, PESGM 2023
Publisher	IEEE Computer Society
ISBN (Electronic)	9781665464413
DOIs	https://doi.org/10.1109/PESGM52003.2023.10252498
Publication status	Published - 2023
Event	2023 IEEE Power and Energy Society General Meeting, PESGM 2023 - Orlando, United States Duration: 2023 Jul 16 → 2023 Jul 20

Publication series

Name	IEEE Power and Energy Society General Meeting
Volume	2023-July
ISSN (Print)	1944-9925
ISSN (Electronic)	1944-9933

Conference

Conference	2023 IEEE Power and Energy Society General Meeting, PESGM 2023
Country/Territory	United States
City	Orlando
Period	23/7/16 → 23/7/20

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy
SDG 13 Climate Action

Keywords

electric vehicle charging station (EVCS)
fast charging station (FCS)
hydrogen energy portfolio standard (HPS)
Hydrogen energy system (HES)

ASJC Scopus subject areas

Energy Engineering and Power Technology
Nuclear Energy and Engineering
Renewable Energy, Sustainability and the Environment
Electrical and Electronic Engineering

Access to Document

10.1109/PESGM52003.2023.10252498

Cite this

Optimal Scheduling Model for Renewable Energy Source-Assisted Electric and Hydrogen Vehicle Charging Station in HPS Market. / Woo, Hyeon; Son, Yongju; Choi, Sungyun.
2023 IEEE Power and Energy Society General Meeting, PESGM 2023. IEEE Computer Society, 2023. (IEEE Power and Energy Society General Meeting; Vol. 2023-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Woo, H, Son, Y & Choi, S 2023, Optimal Scheduling Model for Renewable Energy Source-Assisted Electric and Hydrogen Vehicle Charging Station in HPS Market. in 2023 IEEE Power and Energy Society General Meeting, PESGM 2023. IEEE Power and Energy Society General Meeting, vol. 2023-July, IEEE Computer Society, 2023 IEEE Power and Energy Society General Meeting, PESGM 2023, Orlando, United States, 23/7/16. https://doi.org/10.1109/PESGM52003.2023.10252498

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title = "Optimal Scheduling Model for Renewable Energy Source-Assisted Electric and Hydrogen Vehicle Charging Station in HPS Market",

abstract = "As eco-friendly vehicles, such as electric vehicles (EVs) and hydrogen vehicles (HVs), become more popular, the heavy charging loads due to EV charging stations (EVCSs) and HV charging stations (HVCSs) cause additional challenges in the main grid. In response, the idea of renewable energy source-assisted charging stations, which can be used as cost-effective EV and HV charging stations (EHVCSs), has attracted attention. This paper proposes a framework for the stochastic optimal operation of EHVCSs to reduce the amount of power they need to purchase from the main grid and to maximize their revenues through means such as charging fees and hydrogen energy portfolio standard (HPS) sales. To enhance the profitability of HEVCS, the EHVCS can sell hydrogen into the HPS market by generating power through fuel cells installed in HVCSs. The optimization problem is formulated as a nonlinear programming problem given the nature of AC power flow constraints, which is non-convex. Therefore, the problem is transformed into a convex problem by convexifying the problem using second-order conic programming relaxation.",

keywords = "electric vehicle charging station (EVCS), fast charging station (FCS), hydrogen energy portfolio standard (HPS), Hydrogen energy system (HES)",

author = "Hyeon Woo and Yongju Son and Sungyun Choi",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE Power and Energy Society General Meeting, PESGM 2023 ; Conference date: 16-07-2023 Through 20-07-2023",

year = "2023",

doi = "10.1109/PESGM52003.2023.10252498",

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AU - Woo, Hyeon

AU - Son, Yongju

AU - Choi, Sungyun

PY - 2023

Y1 - 2023

N2 - As eco-friendly vehicles, such as electric vehicles (EVs) and hydrogen vehicles (HVs), become more popular, the heavy charging loads due to EV charging stations (EVCSs) and HV charging stations (HVCSs) cause additional challenges in the main grid. In response, the idea of renewable energy source-assisted charging stations, which can be used as cost-effective EV and HV charging stations (EHVCSs), has attracted attention. This paper proposes a framework for the stochastic optimal operation of EHVCSs to reduce the amount of power they need to purchase from the main grid and to maximize their revenues through means such as charging fees and hydrogen energy portfolio standard (HPS) sales. To enhance the profitability of HEVCS, the EHVCS can sell hydrogen into the HPS market by generating power through fuel cells installed in HVCSs. The optimization problem is formulated as a nonlinear programming problem given the nature of AC power flow constraints, which is non-convex. Therefore, the problem is transformed into a convex problem by convexifying the problem using second-order conic programming relaxation.

AB - As eco-friendly vehicles, such as electric vehicles (EVs) and hydrogen vehicles (HVs), become more popular, the heavy charging loads due to EV charging stations (EVCSs) and HV charging stations (HVCSs) cause additional challenges in the main grid. In response, the idea of renewable energy source-assisted charging stations, which can be used as cost-effective EV and HV charging stations (EHVCSs), has attracted attention. This paper proposes a framework for the stochastic optimal operation of EHVCSs to reduce the amount of power they need to purchase from the main grid and to maximize their revenues through means such as charging fees and hydrogen energy portfolio standard (HPS) sales. To enhance the profitability of HEVCS, the EHVCS can sell hydrogen into the HPS market by generating power through fuel cells installed in HVCSs. The optimization problem is formulated as a nonlinear programming problem given the nature of AC power flow constraints, which is non-convex. Therefore, the problem is transformed into a convex problem by convexifying the problem using second-order conic programming relaxation.

KW - electric vehicle charging station (EVCS)

KW - fast charging station (FCS)

KW - hydrogen energy portfolio standard (HPS)

KW - Hydrogen energy system (HES)

UR - https://www.scopus.com/pages/publications/85174735971

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DO - 10.1109/PESGM52003.2023.10252498

M3 - Conference contribution

AN - SCOPUS:85174735971

T3 - IEEE Power and Energy Society General Meeting

BT - 2023 IEEE Power and Energy Society General Meeting, PESGM 2023

PB - IEEE Computer Society

T2 - 2023 IEEE Power and Energy Society General Meeting, PESGM 2023

Y2 - 16 July 2023 through 20 July 2023

ER -

Optimal Scheduling Model for Renewable Energy Source-Assisted Electric and Hydrogen Vehicle Charging Station in HPS Market

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this