Coordinating vehicle-to-grid services with energy trading

Ali T. Al-Awami; Eric Sortomme

doi:10.1109/TSG.2011.2167992

Coordinating vehicle-to-grid services with energy trading

Ali T. Al-Awami^*
, Eric Sortomme

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

180 Scopus citations

Abstract

Energy trading in day-ahead electricity markets can be highly risky, especially for entities with considerable stochastic energy penetration. This is because of the uncertain energy prices, balancing prices, stochastic energy availability, and demand. In this work, coordinating unidirectional vehicle-to-grid (V2G) services with energy trading is proposed to mitigate these trading risks. This coordination is possible due to the recent advances in smart grid technologies. The case of a load-serving entity (LSE) that owns thermal and wind plants, and is obligated to serve a load with a significant number of electric vehicles (EVs) is investigated. The problem of energy trading in coordination with V2G services is formulated as a mixed-integer stochastic linear program. The objective is to maximize the LSE's profits while maintaining its risks within acceptable levels. The conditional value at risk is used as a risk control measure. A case study that compares coordinated vs. uncoordinated EV charging is presented. The simulation results demonstrate the benefits of coordinating V2G services with other generation assets for the LSE and the EV owners as well as the impact of this coordination on the environment.

Original language	English
Article number	6075307
Pages (from-to)	453-462
Number of pages	10
Journal	IEEE Transactions on Smart Grid
Volume	3
Issue number	1
DOIs	https://doi.org/10.1109/TSG.2011.2167992
State	Published - Mar 2012

Bibliographical note

Funding Information:
Manuscript received March 09, 2011; revised July 24, 2011; accepted August 30, 2011. Date of publication November 10, 2011; date of current version February 23, 2012. This work was supported in part by King Fahd University of Petroleum & Minerals (KFUPM), Dhahran, Saudi Arabia. Paper no. TSG-00095-2011.

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Coordinated bidding strategy
EV charging
V2G
load-serving entities
mixed integer stochastic programming
risk
thermal power production
wind power production

ASJC Scopus subject areas

General Computer Science

Access to Document

10.1109/TSG.2011.2167992

Cite this

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title = "Coordinating vehicle-to-grid services with energy trading",

abstract = "Energy trading in day-ahead electricity markets can be highly risky, especially for entities with considerable stochastic energy penetration. This is because of the uncertain energy prices, balancing prices, stochastic energy availability, and demand. In this work, coordinating unidirectional vehicle-to-grid (V2G) services with energy trading is proposed to mitigate these trading risks. This coordination is possible due to the recent advances in smart grid technologies. The case of a load-serving entity (LSE) that owns thermal and wind plants, and is obligated to serve a load with a significant number of electric vehicles (EVs) is investigated. The problem of energy trading in coordination with V2G services is formulated as a mixed-integer stochastic linear program. The objective is to maximize the LSE's profits while maintaining its risks within acceptable levels. The conditional value at risk is used as a risk control measure. A case study that compares coordinated vs. uncoordinated EV charging is presented. The simulation results demonstrate the benefits of coordinating V2G services with other generation assets for the LSE and the EV owners as well as the impact of this coordination on the environment.",

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author = "Al-Awami, \{Ali T.\} and Eric Sortomme",

note = "Funding Information: Manuscript received March 09, 2011; revised July 24, 2011; accepted August 30, 2011. Date of publication November 10, 2011; date of current version February 23, 2012. This work was supported in part by King Fahd University of Petroleum \& Minerals (KFUPM), Dhahran, Saudi Arabia. Paper no. TSG-00095-2011.",

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N2 - Energy trading in day-ahead electricity markets can be highly risky, especially for entities with considerable stochastic energy penetration. This is because of the uncertain energy prices, balancing prices, stochastic energy availability, and demand. In this work, coordinating unidirectional vehicle-to-grid (V2G) services with energy trading is proposed to mitigate these trading risks. This coordination is possible due to the recent advances in smart grid technologies. The case of a load-serving entity (LSE) that owns thermal and wind plants, and is obligated to serve a load with a significant number of electric vehicles (EVs) is investigated. The problem of energy trading in coordination with V2G services is formulated as a mixed-integer stochastic linear program. The objective is to maximize the LSE's profits while maintaining its risks within acceptable levels. The conditional value at risk is used as a risk control measure. A case study that compares coordinated vs. uncoordinated EV charging is presented. The simulation results demonstrate the benefits of coordinating V2G services with other generation assets for the LSE and the EV owners as well as the impact of this coordination on the environment.

AB - Energy trading in day-ahead electricity markets can be highly risky, especially for entities with considerable stochastic energy penetration. This is because of the uncertain energy prices, balancing prices, stochastic energy availability, and demand. In this work, coordinating unidirectional vehicle-to-grid (V2G) services with energy trading is proposed to mitigate these trading risks. This coordination is possible due to the recent advances in smart grid technologies. The case of a load-serving entity (LSE) that owns thermal and wind plants, and is obligated to serve a load with a significant number of electric vehicles (EVs) is investigated. The problem of energy trading in coordination with V2G services is formulated as a mixed-integer stochastic linear program. The objective is to maximize the LSE's profits while maintaining its risks within acceptable levels. The conditional value at risk is used as a risk control measure. A case study that compares coordinated vs. uncoordinated EV charging is presented. The simulation results demonstrate the benefits of coordinating V2G services with other generation assets for the LSE and the EV owners as well as the impact of this coordination on the environment.

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KW - wind power production

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M3 - Article

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Coordinating vehicle-to-grid services with energy trading

Abstract

Bibliographical note

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this