Stochastic charging coordination method for electric vehicle (EV) aggregator considering uncertainty in EV departures

Youngwook Kim; Seongbae Kong; Sung Kwan Joo

doi:10.5370/JEET.2016.11.5.1049

Stochastic charging coordination method for electric vehicle (EV) aggregator considering uncertainty in EV departures

Youngwook Kim, Seongbae Kong, Sung Kwan Joo

School of Electrical Engineering

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

4 Citations (Scopus)

Abstract

This paper presents a stochastic method for an electric vehicle (EV) aggregator to coordinate EV charging schedule considering uncertainty in EV departures. The EV aggregator is responsible for managing the charging schedule of EVs while participating in the electricity markets. The managed EV charging can provide additional revenues to the aggregator from regulation market participation and charging cost reductions to EV owners. The aggregator needs to coordinate the charging schedule considering various uncertain factors such as electricity market prices and the stochastic characteristics of EVs. In this paper, the EV charging scheduling problem incorporating uncertainty in EV departures is formulated as a stochastic optimization problem. A stochastic optimization method is used to solve the EV charging scheduling problem. Latin hypercube sampling (LHS) and a scenario-reduction method are also applied to reduce the computational efforts of the proposed method. The results of a numerical example are presented to show the effectiveness of the proposed stochastic EV charging coordination method.

Original language	English
Pages (from-to)	1049-1056
Number of pages	8
Journal	Journal of Electrical Engineering and Technology
Volume	11
Issue number	5
DOIs	https://doi.org/10.5370/JEET.2016.11.5.1049
Publication status	Published - 2016 Sep

Keywords

EV aggregator
Electrical vehicle
Regulation
Stochastic EV departure

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.5370/JEET.2016.11.5.1049

Cite this

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title = "Stochastic charging coordination method for electric vehicle (EV) aggregator considering uncertainty in EV departures",

abstract = "This paper presents a stochastic method for an electric vehicle (EV) aggregator to coordinate EV charging schedule considering uncertainty in EV departures. The EV aggregator is responsible for managing the charging schedule of EVs while participating in the electricity markets. The managed EV charging can provide additional revenues to the aggregator from regulation market participation and charging cost reductions to EV owners. The aggregator needs to coordinate the charging schedule considering various uncertain factors such as electricity market prices and the stochastic characteristics of EVs. In this paper, the EV charging scheduling problem incorporating uncertainty in EV departures is formulated as a stochastic optimization problem. A stochastic optimization method is used to solve the EV charging scheduling problem. Latin hypercube sampling (LHS) and a scenario-reduction method are also applied to reduce the computational efforts of the proposed method. The results of a numerical example are presented to show the effectiveness of the proposed stochastic EV charging coordination method.",

keywords = "EV aggregator, Electrical vehicle, Regulation, Stochastic EV departure",

author = "Youngwook Kim and Seongbae Kong and Joo, {Sung Kwan}",

note = "Funding Information: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2013R1A1A2057969). This work was supported by ?Human Resources program in Energy Technology? of the Korea Institute of Energy Technology Evaluation and Planning(KETEP) granted financial resource from the Ministry of Trade, Industry & Energy, Republic of Korea (No. 20154030200610). Publisher Copyright: {\textcopyright} The Korean Institute of Electrical Engineers.",

year = "2016",

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AU - Joo, Sung Kwan

N1 - Funding Information: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2013R1A1A2057969). This work was supported by ?Human Resources program in Energy Technology? of the Korea Institute of Energy Technology Evaluation and Planning(KETEP) granted financial resource from the Ministry of Trade, Industry & Energy, Republic of Korea (No. 20154030200610). Publisher Copyright: © The Korean Institute of Electrical Engineers.

PY - 2016/9

Y1 - 2016/9

N2 - This paper presents a stochastic method for an electric vehicle (EV) aggregator to coordinate EV charging schedule considering uncertainty in EV departures. The EV aggregator is responsible for managing the charging schedule of EVs while participating in the electricity markets. The managed EV charging can provide additional revenues to the aggregator from regulation market participation and charging cost reductions to EV owners. The aggregator needs to coordinate the charging schedule considering various uncertain factors such as electricity market prices and the stochastic characteristics of EVs. In this paper, the EV charging scheduling problem incorporating uncertainty in EV departures is formulated as a stochastic optimization problem. A stochastic optimization method is used to solve the EV charging scheduling problem. Latin hypercube sampling (LHS) and a scenario-reduction method are also applied to reduce the computational efforts of the proposed method. The results of a numerical example are presented to show the effectiveness of the proposed stochastic EV charging coordination method.

AB - This paper presents a stochastic method for an electric vehicle (EV) aggregator to coordinate EV charging schedule considering uncertainty in EV departures. The EV aggregator is responsible for managing the charging schedule of EVs while participating in the electricity markets. The managed EV charging can provide additional revenues to the aggregator from regulation market participation and charging cost reductions to EV owners. The aggregator needs to coordinate the charging schedule considering various uncertain factors such as electricity market prices and the stochastic characteristics of EVs. In this paper, the EV charging scheduling problem incorporating uncertainty in EV departures is formulated as a stochastic optimization problem. A stochastic optimization method is used to solve the EV charging scheduling problem. Latin hypercube sampling (LHS) and a scenario-reduction method are also applied to reduce the computational efforts of the proposed method. The results of a numerical example are presented to show the effectiveness of the proposed stochastic EV charging coordination method.

KW - EV aggregator

KW - Electrical vehicle

KW - Regulation

KW - Stochastic EV departure

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Stochastic charging coordination method for electric vehicle (EV) aggregator considering uncertainty in EV departures

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Keywords

ASJC Scopus subject areas

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