Robust mean-variance optimization model for grid-connected microgrids

Linquan Bai; Qinran Hu; Fangxing Li; Tao Ding; Hongbin Sun

doi:10.1109/PESGM.2015.7286489

Robust mean-variance optimization model for grid-connected microgrids

Linquan Bai
, Qinran Hu
, Fangxing Li
, Tao Ding
, Hongbin Sun

University of Tennessee
Tsinghua University

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

16 Scopus citations

Abstract

This paper proposes a mean-variance optimization model for the grid-connected microgrid energy management system (MG-EMS). In the proposed method, both the expected system operating cost and the tie-line power fluctuation variance are taken as the objective functions to provide a trade-off between operating benefit and risk assessment for decision makers. Further, robust optimization (RO) has been applied to eliminate the potential reliability issue due to wind power uncertainty. Therefore, the proposed method can effectively generate a robust optimal day-ahead operating schedule for wind power, energy storage (ES), and load management under worst-case scenarios in the microgrid. Finally, the case study on a revised IEEE 14-bus system has been implemented to demonstrate the validity and effectiveness of the proposed method.

Original language	English
Title of host publication	2015 IEEE Power and Energy Society General Meeting, PESGM 2015
Publisher	IEEE Computer Society
ISBN (Electronic)	9781467380409
DOIs	https://doi.org/10.1109/PESGM.2015.7286489
State	Published - 30 Sep 2015
Externally published	Yes
Event	IEEE Power and Energy Society General Meeting, PESGM 2015 - Denver, United States Duration: 26 Jul 2015 → 30 Jul 2015

Publication series

Name	IEEE Power and Energy Society General Meeting
Volume	2015-September
ISSN (Print)	1944-9925
ISSN (Electronic)	1944-9933

Conference

Conference	IEEE Power and Energy Society General Meeting, PESGM 2015
Country/Territory	United States
City	Denver
Period	26/07/15 → 30/07/15

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Energy management system (EMS)
mean-variance model
microgrid
robust optimization (RO)

Access to Document

10.1109/PESGM.2015.7286489

Cite this

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title = "Robust mean-variance optimization model for grid-connected microgrids",

abstract = "This paper proposes a mean-variance optimization model for the grid-connected microgrid energy management system (MG-EMS). In the proposed method, both the expected system operating cost and the tie-line power fluctuation variance are taken as the objective functions to provide a trade-off between operating benefit and risk assessment for decision makers. Further, robust optimization (RO) has been applied to eliminate the potential reliability issue due to wind power uncertainty. Therefore, the proposed method can effectively generate a robust optimal day-ahead operating schedule for wind power, energy storage (ES), and load management under worst-case scenarios in the microgrid. Finally, the case study on a revised IEEE 14-bus system has been implemented to demonstrate the validity and effectiveness of the proposed method.",

keywords = "Energy management system (EMS), mean-variance model, microgrid, robust optimization (RO)",

author = "Linquan Bai and Qinran Hu and Fangxing Li and Tao Ding and Hongbin Sun",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE Power and Energy Society General Meeting, PESGM 2015 ; Conference date: 26-07-2015 Through 30-07-2015",

year = "2015",

month = sep,

day = "30",

doi = "10.1109/PESGM.2015.7286489",

language = "英语",

series = "IEEE Power and Energy Society General Meeting",

publisher = "IEEE Computer Society",

booktitle = "2015 IEEE Power and Energy Society General Meeting, PESGM 2015",

}

Bai, L, Hu, Q, Li, F, Ding, T & Sun, H 2015, Robust mean-variance optimization model for grid-connected microgrids. in 2015 IEEE Power and Energy Society General Meeting, PESGM 2015., 7286489, IEEE Power and Energy Society General Meeting, vol. 2015-September, IEEE Computer Society, IEEE Power and Energy Society General Meeting, PESGM 2015, Denver, United States, 26/07/15. https://doi.org/10.1109/PESGM.2015.7286489

Robust mean-variance optimization model for grid-connected microgrids. / Bai, Linquan; Hu, Qinran; Li, Fangxing et al.
2015 IEEE Power and Energy Society General Meeting, PESGM 2015. IEEE Computer Society, 2015. 7286489 (IEEE Power and Energy Society General Meeting; Vol. 2015-September).

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

TY - GEN

T1 - Robust mean-variance optimization model for grid-connected microgrids

AU - Bai, Linquan

AU - Hu, Qinran

AU - Li, Fangxing

AU - Ding, Tao

AU - Sun, Hongbin

PY - 2015/9/30

Y1 - 2015/9/30

N2 - This paper proposes a mean-variance optimization model for the grid-connected microgrid energy management system (MG-EMS). In the proposed method, both the expected system operating cost and the tie-line power fluctuation variance are taken as the objective functions to provide a trade-off between operating benefit and risk assessment for decision makers. Further, robust optimization (RO) has been applied to eliminate the potential reliability issue due to wind power uncertainty. Therefore, the proposed method can effectively generate a robust optimal day-ahead operating schedule for wind power, energy storage (ES), and load management under worst-case scenarios in the microgrid. Finally, the case study on a revised IEEE 14-bus system has been implemented to demonstrate the validity and effectiveness of the proposed method.

AB - This paper proposes a mean-variance optimization model for the grid-connected microgrid energy management system (MG-EMS). In the proposed method, both the expected system operating cost and the tie-line power fluctuation variance are taken as the objective functions to provide a trade-off between operating benefit and risk assessment for decision makers. Further, robust optimization (RO) has been applied to eliminate the potential reliability issue due to wind power uncertainty. Therefore, the proposed method can effectively generate a robust optimal day-ahead operating schedule for wind power, energy storage (ES), and load management under worst-case scenarios in the microgrid. Finally, the case study on a revised IEEE 14-bus system has been implemented to demonstrate the validity and effectiveness of the proposed method.

KW - Energy management system (EMS)

KW - mean-variance model

KW - microgrid

KW - robust optimization (RO)

UR - https://www.scopus.com/pages/publications/84956865060

U2 - 10.1109/PESGM.2015.7286489

DO - 10.1109/PESGM.2015.7286489

M3 - 会议稿件

AN - SCOPUS:84956865060

T3 - IEEE Power and Energy Society General Meeting

BT - 2015 IEEE Power and Energy Society General Meeting, PESGM 2015

PB - IEEE Computer Society

T2 - IEEE Power and Energy Society General Meeting, PESGM 2015

Y2 - 26 July 2015 through 30 July 2015

ER -

Robust mean-variance optimization model for grid-connected microgrids

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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