Clustering consumption in queues: A scalable model for electric vehicle scheduling

Mahnoosh Alizadeh; George Kesidis; Anna Scaglione

doi:10.1109/ACSSC.2013.6810299

Clustering consumption in queues: A scalable model for electric vehicle scheduling

Mahnoosh Alizadeh
, George Kesidis
, Anna Scaglione

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

6 Scopus citations

Abstract

In this paper, we introduce a scalable model for the aggregate electricity demand of a fleet of electric vehicles, which can provide the right balance between model simplicity and accuracy. The model is based on classification of tasks with similar energy consumption characteristics into a finite number of clusters. The aggregator responsible for scheduling the charge of the vehicles has two goals: 1) to provide a hard QoS guarantee to the vehicles at the lowest possible cost; 2) to offer load or generation following services to the wholesale market. In order to achieve these goals, we combine the scalable demand model we propose with two scheduling mechanisms, a near-optimal and a heuristic technique. The performance of the two mechanisms is compared under a realistic setting in our numerical experiments.

Original language	English (US)
Title of host publication	Conference Record of the 47th Asilomar Conference on Signals, Systems and Computers
Publisher	IEEE Computer Society
Pages	374-378
Number of pages	5
ISBN (Print)	9781479923908
DOIs	https://doi.org/10.1109/ACSSC.2013.6810299
State	Published - 2013
Event	47th Asilomar Conference on Signals, Systems and Computers, ACSSC 2013 - Pacific Grove, CA, United States Duration: Nov 3 2013 → Nov 6 2013

Publication series

Name	Conference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)	1058-6393

Conference

Conference	47th Asilomar Conference on Signals, Systems and Computers, ACSSC 2013
Country/Territory	United States
City	Pacific Grove, CA
Period	11/3/13 → 11/6/13

UN SDGs

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

SDG 7 Affordable and Clean Energy

All Science Journal Classification (ASJC) codes

Signal Processing
Computer Networks and Communications

Access to Document

10.1109/ACSSC.2013.6810299

Cite this

Alizadeh, M., Kesidis, G., & Scaglione, A. (2013). Clustering consumption in queues: A scalable model for electric vehicle scheduling. In Conference Record of the 47th Asilomar Conference on Signals, Systems and Computers (pp. 374-378). Article 6810299 (Conference Record - Asilomar Conference on Signals, Systems and Computers). IEEE Computer Society. https://doi.org/10.1109/ACSSC.2013.6810299

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title = "Clustering consumption in queues: A scalable model for electric vehicle scheduling",

abstract = "In this paper, we introduce a scalable model for the aggregate electricity demand of a fleet of electric vehicles, which can provide the right balance between model simplicity and accuracy. The model is based on classification of tasks with similar energy consumption characteristics into a finite number of clusters. The aggregator responsible for scheduling the charge of the vehicles has two goals: 1) to provide a hard QoS guarantee to the vehicles at the lowest possible cost; 2) to offer load or generation following services to the wholesale market. In order to achieve these goals, we combine the scalable demand model we propose with two scheduling mechanisms, a near-optimal and a heuristic technique. The performance of the two mechanisms is compared under a realistic setting in our numerical experiments.",

author = "Mahnoosh Alizadeh and George Kesidis and Anna Scaglione",

year = "2013",

doi = "10.1109/ACSSC.2013.6810299",

language = "English (US)",

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series = "Conference Record - Asilomar Conference on Signals, Systems and Computers",

publisher = "IEEE Computer Society",

pages = "374--378",

booktitle = "Conference Record of the 47th Asilomar Conference on Signals, Systems and Computers",

address = "United States",

note = "47th Asilomar Conference on Signals, Systems and Computers, ACSSC 2013 ; Conference date: 03-11-2013 Through 06-11-2013",

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Alizadeh, M, Kesidis, G & Scaglione, A 2013, Clustering consumption in queues: A scalable model for electric vehicle scheduling. in Conference Record of the 47th Asilomar Conference on Signals, Systems and Computers., 6810299, Conference Record - Asilomar Conference on Signals, Systems and Computers, IEEE Computer Society, pp. 374-378, 47th Asilomar Conference on Signals, Systems and Computers, ACSSC 2013, Pacific Grove, CA, United States, 11/3/13. https://doi.org/10.1109/ACSSC.2013.6810299

Clustering consumption in queues: A scalable model for electric vehicle scheduling. / Alizadeh, Mahnoosh; Kesidis, George; Scaglione, Anna.
Conference Record of the 47th Asilomar Conference on Signals, Systems and Computers. IEEE Computer Society, 2013. p. 374-378 6810299 (Conference Record - Asilomar Conference on Signals, Systems and Computers).

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

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T1 - Clustering consumption in queues

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N2 - In this paper, we introduce a scalable model for the aggregate electricity demand of a fleet of electric vehicles, which can provide the right balance between model simplicity and accuracy. The model is based on classification of tasks with similar energy consumption characteristics into a finite number of clusters. The aggregator responsible for scheduling the charge of the vehicles has two goals: 1) to provide a hard QoS guarantee to the vehicles at the lowest possible cost; 2) to offer load or generation following services to the wholesale market. In order to achieve these goals, we combine the scalable demand model we propose with two scheduling mechanisms, a near-optimal and a heuristic technique. The performance of the two mechanisms is compared under a realistic setting in our numerical experiments.

AB - In this paper, we introduce a scalable model for the aggregate electricity demand of a fleet of electric vehicles, which can provide the right balance between model simplicity and accuracy. The model is based on classification of tasks with similar energy consumption characteristics into a finite number of clusters. The aggregator responsible for scheduling the charge of the vehicles has two goals: 1) to provide a hard QoS guarantee to the vehicles at the lowest possible cost; 2) to offer load or generation following services to the wholesale market. In order to achieve these goals, we combine the scalable demand model we propose with two scheduling mechanisms, a near-optimal and a heuristic technique. The performance of the two mechanisms is compared under a realistic setting in our numerical experiments.

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Y2 - 3 November 2013 through 6 November 2013

ER -

Clustering consumption in queues: A scalable model for electric vehicle scheduling

Abstract

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UN SDGs

All Science Journal Classification (ASJC) codes

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