Chance-constrained transmission expansion planning with guaranteed wind power utilization

Yao Zhang; Jianxue Wang; Yunhao Li; Xiaoyu Cao

doi:10.1109/PESGM.2017.8274146

Chance-constrained transmission expansion planning with guaranteed wind power utilization

Yao Zhang
, Jianxue Wang
, Yunhao Li
, Xiaoyu Cao

Xi'an Jiaotong University

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

6 Scopus citations

Abstract

In this paper, we study N-1 contingency-constrained transmission expansion planning (TEP) problems considering the uncertainty of wind power output. TEP problem is formulated as a chance-constrained stochastic programming. Our model ensures that a large portion of wind power generation will be utilized with a high probability. Furthermore, we present a bilinear mixed integer formulation of chance constraint, and then derive its linear counterpart. Finally, the computational result indicates that increasing the utilization portion of wind power generation may increase the total investment cost of transmission lines. Our experiments also verify that the bilinear mixed integer formulation is stronger than the widely adopted Big-M linear formulation.

Original language	English
Title of host publication	2017 IEEE Power and Energy Society General Meeting, PESGM 2017
Publisher	IEEE Computer Society
Pages	1-5
Number of pages	5
ISBN (Electronic)	9781538622124
DOIs	https://doi.org/10.1109/PESGM.2017.8274146
State	Published - 29 Jan 2018
Event	2017 IEEE Power and Energy Society General Meeting, PESGM 2017 - Chicago, United States Duration: 16 Jul 2017 → 20 Jul 2017

Publication series

Name	IEEE Power and Energy Society General Meeting
Volume	2018-January
ISSN (Print)	1944-9925
ISSN (Electronic)	1944-9933

Conference

Conference	2017 IEEE Power and Energy Society General Meeting, PESGM 2017
Country/Territory	United States
City	Chicago
Period	16/07/17 → 20/07/17

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Bilinear formulation
Chance constraints
Mixed integer programming
Stochastic programming
Transmission expansion planning
Wind power

Access to Document

10.1109/PESGM.2017.8274146

Cite this

@inproceedings{da906e5e9a4045cb8248f13c6a37534a,

title = "Chance-constrained transmission expansion planning with guaranteed wind power utilization",

abstract = "In this paper, we study N-1 contingency-constrained transmission expansion planning (TEP) problems considering the uncertainty of wind power output. TEP problem is formulated as a chance-constrained stochastic programming. Our model ensures that a large portion of wind power generation will be utilized with a high probability. Furthermore, we present a bilinear mixed integer formulation of chance constraint, and then derive its linear counterpart. Finally, the computational result indicates that increasing the utilization portion of wind power generation may increase the total investment cost of transmission lines. Our experiments also verify that the bilinear mixed integer formulation is stronger than the widely adopted Big-M linear formulation.",

keywords = "Bilinear formulation, Chance constraints, Mixed integer programming, Stochastic programming, Transmission expansion planning, Wind power",

author = "Yao Zhang and Jianxue Wang and Yunhao Li and Xiaoyu Cao",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE Power and Energy Society General Meeting, PESGM 2017 ; Conference date: 16-07-2017 Through 20-07-2017",

year = "2018",

month = jan,

day = "29",

doi = "10.1109/PESGM.2017.8274146",

language = "英语",

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

publisher = "IEEE Computer Society",

pages = "1--5",

booktitle = "2017 IEEE Power and Energy Society General Meeting, PESGM 2017",

}

Zhang, Y, Wang, J, Li, Y & Cao, X 2018, Chance-constrained transmission expansion planning with guaranteed wind power utilization. in 2017 IEEE Power and Energy Society General Meeting, PESGM 2017. IEEE Power and Energy Society General Meeting, vol. 2018-January, IEEE Computer Society, pp. 1-5, 2017 IEEE Power and Energy Society General Meeting, PESGM 2017, Chicago, United States, 16/07/17. https://doi.org/10.1109/PESGM.2017.8274146

Chance-constrained transmission expansion planning with guaranteed wind power utilization. / Zhang, Yao; Wang, Jianxue; Li, Yunhao et al.
2017 IEEE Power and Energy Society General Meeting, PESGM 2017. IEEE Computer Society, 2018. p. 1-5 (IEEE Power and Energy Society General Meeting; Vol. 2018-January).

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

TY - GEN

T1 - Chance-constrained transmission expansion planning with guaranteed wind power utilization

AU - Zhang, Yao

AU - Wang, Jianxue

AU - Li, Yunhao

AU - Cao, Xiaoyu

PY - 2018/1/29

Y1 - 2018/1/29

N2 - In this paper, we study N-1 contingency-constrained transmission expansion planning (TEP) problems considering the uncertainty of wind power output. TEP problem is formulated as a chance-constrained stochastic programming. Our model ensures that a large portion of wind power generation will be utilized with a high probability. Furthermore, we present a bilinear mixed integer formulation of chance constraint, and then derive its linear counterpart. Finally, the computational result indicates that increasing the utilization portion of wind power generation may increase the total investment cost of transmission lines. Our experiments also verify that the bilinear mixed integer formulation is stronger than the widely adopted Big-M linear formulation.

AB - In this paper, we study N-1 contingency-constrained transmission expansion planning (TEP) problems considering the uncertainty of wind power output. TEP problem is formulated as a chance-constrained stochastic programming. Our model ensures that a large portion of wind power generation will be utilized with a high probability. Furthermore, we present a bilinear mixed integer formulation of chance constraint, and then derive its linear counterpart. Finally, the computational result indicates that increasing the utilization portion of wind power generation may increase the total investment cost of transmission lines. Our experiments also verify that the bilinear mixed integer formulation is stronger than the widely adopted Big-M linear formulation.

KW - Bilinear formulation

KW - Chance constraints

KW - Mixed integer programming

KW - Stochastic programming

KW - Transmission expansion planning

KW - Wind power

UR - https://www.scopus.com/pages/publications/85046370174

U2 - 10.1109/PESGM.2017.8274146

DO - 10.1109/PESGM.2017.8274146

M3 - 会议稿件

AN - SCOPUS:85046370174

T3 - IEEE Power and Energy Society General Meeting

SP - 1

EP - 5

BT - 2017 IEEE Power and Energy Society General Meeting, PESGM 2017

PB - IEEE Computer Society

T2 - 2017 IEEE Power and Energy Society General Meeting, PESGM 2017

Y2 - 16 July 2017 through 20 July 2017

ER -

Chance-constrained transmission expansion planning with guaranteed wind power utilization

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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Cite this