Demand response of data centers: A real-time pricing game between utilities in smart grid

Nguyen H. Tran; Shaolei Ren; Zhu Han; Sung Man Jang; Seung Il Moon; Choong Seon Hong

Demand response of data centers: A real-time pricing game between utilities in smart grid

Nguyen H. Tran, Shaolei Ren, Zhu Han, Sung Man Jang, Seung Il Moon, Choong Seon Hong

Research output: Contribution to conference › Paper › peer-review

14 Citations (Scopus)

Abstract

We study the demand response (DR) of geo-distributed data centers (DCs) using a dynamic pricing scheme. Our proposed pricing scheme is constructed based on a formulated two-stage Stackelberg game where each utility sets a real-time price to maximize its own profit in Stage I; and based on these prices, the DCs' service provider minimizes its cost via workload shifting and dynamic server allocation in Stage II. First, we show that there exists a unique Stackelberg equilibrium. Then, we propose an iterative and distributed algorithm that converges to this equilibrium, where the “right prices” are set for the “right demand”. Finally, we verify our proposal by traced-base simulation and results show that our pricing scheme outperforms other baseline schemes significantly.

Original language	English
Publication status	Published - 2014
Event	9th International Workshop on Feedback Computing - Philadelphia, United States Duration: 17 Jun 2014 → 20 Jun 2014

Conference

Conference	9th International Workshop on Feedback Computing
Country/Territory	United States
City	Philadelphia
Period	17/06/14 → 20/06/14

Bibliographical note

Publisher Copyright:
© 9th International Workshop on Feedback Computing 2014. All rights reserved.

UN SDGs

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

Cite this

@conference{712dac7d1f7148c596ae9ef53d8195ed,

title = "Demand response of data centers: A real-time pricing game between utilities in smart grid",

abstract = "We study the demand response (DR) of geo-distributed data centers (DCs) using a dynamic pricing scheme. Our proposed pricing scheme is constructed based on a formulated two-stage Stackelberg game where each utility sets a real-time price to maximize its own profit in Stage I; and based on these prices, the DCs' service provider minimizes its cost via workload shifting and dynamic server allocation in Stage II. First, we show that there exists a unique Stackelberg equilibrium. Then, we propose an iterative and distributed algorithm that converges to this equilibrium, where the “right prices” are set for the “right demand”. Finally, we verify our proposal by traced-base simulation and results show that our pricing scheme outperforms other baseline schemes significantly.",

author = "Tran, {Nguyen H.} and Shaolei Ren and Zhu Han and Jang, {Sung Man} and Moon, {Seung Il} and Hong, {Choong Seon}",

note = "Publisher Copyright: {\textcopyright} 9th International Workshop on Feedback Computing 2014. All rights reserved.; 9th International Workshop on Feedback Computing ; Conference date: 17-06-2014 Through 20-06-2014",

year = "2014",

language = "English",

}

TY - CONF

T1 - Demand response of data centers

T2 - 9th International Workshop on Feedback Computing

AU - Tran, Nguyen H.

AU - Ren, Shaolei

AU - Han, Zhu

AU - Jang, Sung Man

AU - Moon, Seung Il

AU - Hong, Choong Seon

PY - 2014

Y1 - 2014

N2 - We study the demand response (DR) of geo-distributed data centers (DCs) using a dynamic pricing scheme. Our proposed pricing scheme is constructed based on a formulated two-stage Stackelberg game where each utility sets a real-time price to maximize its own profit in Stage I; and based on these prices, the DCs' service provider minimizes its cost via workload shifting and dynamic server allocation in Stage II. First, we show that there exists a unique Stackelberg equilibrium. Then, we propose an iterative and distributed algorithm that converges to this equilibrium, where the “right prices” are set for the “right demand”. Finally, we verify our proposal by traced-base simulation and results show that our pricing scheme outperforms other baseline schemes significantly.

AB - We study the demand response (DR) of geo-distributed data centers (DCs) using a dynamic pricing scheme. Our proposed pricing scheme is constructed based on a formulated two-stage Stackelberg game where each utility sets a real-time price to maximize its own profit in Stage I; and based on these prices, the DCs' service provider minimizes its cost via workload shifting and dynamic server allocation in Stage II. First, we show that there exists a unique Stackelberg equilibrium. Then, we propose an iterative and distributed algorithm that converges to this equilibrium, where the “right prices” are set for the “right demand”. Finally, we verify our proposal by traced-base simulation and results show that our pricing scheme outperforms other baseline schemes significantly.

UR - http://www.scopus.com/inward/record.url?scp=85091955324&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:85091955324

Y2 - 17 June 2014 through 20 June 2014

ER -

Demand response of data centers: A real-time pricing game between utilities in smart grid

Abstract

Conference

Bibliographical note

UN SDGs

Other files and links

Fingerprint

Cite this