A comparison of scenario generation methods for the participation of electric vehicles in electricity markets

Research output: Contribution to journalJournal article – Annual report year: 2019Researchpeer-review

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A comparison of scenario generation methods for the participation of electric vehicles in electricity markets. / Jensen, Ida Græsted; Møller, Niels Framroze; Pantuso, Giovanni; Juul, Nina.

In: International Transactions on Electrical Energy Systems, Vol. 29, No. 4, e2782, 2019.

Research output: Contribution to journalJournal article – Annual report year: 2019Researchpeer-review

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@article{faef03a1f07b4c4498d83303b0d6a2d8,
title = "A comparison of scenario generation methods for the participation of electric vehicles in electricity markets",
abstract = "We consider the procurement of electricity for a large fleet of electric vehicles operating in electricity markets. Due to uncertain regulating prices, this problem has typically been modelled as a stochastic program. In this study, we address the issue of generating scenario trees, ie, simplified representations of the uncertainty necessary to solve the corresponding stochastic programs. A trade‐off between accurate descriptions of the uncertainty and tractability of the stochastic program is sought. Based on data describing electric mobility and electricity prices in Denmark, general‐purpose scenario generation strategies are tested and compared. Such strategies include state‐of‐the‐art property matching methods and time‐series analysis. The results show that the co‐dependence between the regulating prices at different hours of the day plays a crucial role when generating scenario trees for these problems, making copulas an important property to consider. This information can help decision makers to achieve better (cheaper) electricity procurement by accurately preprocessing the uncertainty in the regulating prices.",
keywords = "Electric vehicles, Regulating market, Stochastic programming, Scenario generation",
author = "Jensen, {Ida Gr{\ae}sted} and M{\o}ller, {Niels Framroze} and Giovanni Pantuso and Nina Juul",
year = "2019",
doi = "10.1002/etep.2782",
language = "English",
volume = "29",
journal = "International Transactions on Electrical Energy Systems",
issn = "1430-144X",
publisher = "Wiley",
number = "4",

}

RIS

TY - JOUR

T1 - A comparison of scenario generation methods for the participation of electric vehicles in electricity markets

AU - Jensen, Ida Græsted

AU - Møller, Niels Framroze

AU - Pantuso, Giovanni

AU - Juul, Nina

PY - 2019

Y1 - 2019

N2 - We consider the procurement of electricity for a large fleet of electric vehicles operating in electricity markets. Due to uncertain regulating prices, this problem has typically been modelled as a stochastic program. In this study, we address the issue of generating scenario trees, ie, simplified representations of the uncertainty necessary to solve the corresponding stochastic programs. A trade‐off between accurate descriptions of the uncertainty and tractability of the stochastic program is sought. Based on data describing electric mobility and electricity prices in Denmark, general‐purpose scenario generation strategies are tested and compared. Such strategies include state‐of‐the‐art property matching methods and time‐series analysis. The results show that the co‐dependence between the regulating prices at different hours of the day plays a crucial role when generating scenario trees for these problems, making copulas an important property to consider. This information can help decision makers to achieve better (cheaper) electricity procurement by accurately preprocessing the uncertainty in the regulating prices.

AB - We consider the procurement of electricity for a large fleet of electric vehicles operating in electricity markets. Due to uncertain regulating prices, this problem has typically been modelled as a stochastic program. In this study, we address the issue of generating scenario trees, ie, simplified representations of the uncertainty necessary to solve the corresponding stochastic programs. A trade‐off between accurate descriptions of the uncertainty and tractability of the stochastic program is sought. Based on data describing electric mobility and electricity prices in Denmark, general‐purpose scenario generation strategies are tested and compared. Such strategies include state‐of‐the‐art property matching methods and time‐series analysis. The results show that the co‐dependence between the regulating prices at different hours of the day plays a crucial role when generating scenario trees for these problems, making copulas an important property to consider. This information can help decision makers to achieve better (cheaper) electricity procurement by accurately preprocessing the uncertainty in the regulating prices.

KW - Electric vehicles

KW - Regulating market

KW - Stochastic programming

KW - Scenario generation

U2 - 10.1002/etep.2782

DO - 10.1002/etep.2782

M3 - Journal article

VL - 29

JO - International Transactions on Electrical Energy Systems

JF - International Transactions on Electrical Energy Systems

SN - 1430-144X

IS - 4

M1 - e2782

ER -