Optimal allocation of static var compensator via mixed integer conic programming

Xiaohu Zhang; Di Shi; Zhiwei Wang; Junhui Huang; Xu Wang; Guodong Liu; Kevin Tomsovic

doi:10.1109/PESGM.2017.8274057

Optimal allocation of static var compensator via mixed integer conic programming

Xiaohu Zhang, Di Shi, Zhiwei Wang, Junhui Huang, Xu Wang, Guodong Liu, Kevin Tomsovic

Grid Systems Architecture

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

3 Scopus citations

Abstract

Shunt FACTS devices, such as, a Static Var Compensator (SVC), are capable of providing local reactive power compensation. They are widely used in the network to reduce the real power loss and improve the voltage profile. This paper proposes a planning model based on mixed integer conic programming (MICP) to optimally allocate SVCs in the transmission network considering load uncertainty. The load uncertainties are represented by a number of scenarios. Reformulation and linearization techniques are utilized to transform the original non-convex model into a convex second order cone programming (SOCP) model. Numerical case studies based on the IEEE 30-bus system demonstrate the effectiveness of the proposed planning model.

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.2017.8274057
State	Published - Jan 29 2018
Event	2017 IEEE Power and Energy Society General Meeting, PESGM 2017 - Chicago, United States Duration: Jul 16 2017 → Jul 20 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	07/16/17 → 07/20/17

Funding

This work was supported in part by ARPAe (Advanced Research Projects Agency Energy), and in part by the Engineering Research Center Program of the National Science Foundation and the Department of Energy under NSF Award Number EEC-1041877 and the CURENT Industry Partnership Program.

Funders	Funder number
National Science Foundation	EEC-1041877
U.S. Department of Energy
Directorate for Engineering	1041877
Advanced Research Projects Agency - Energy

Keywords

Load uncertainties
Mixed integer conic programming (MICP)
Optimization
SVC allocation
Transmission network

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10.1109/PESGM.2017.8274057

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Zhang, X., Shi, D., Wang, Z., Huang, J., Wang, X., Liu, G., & Tomsovic, K. (2018). Optimal allocation of static var compensator via mixed integer conic programming. In 2017 IEEE Power and Energy Society General Meeting, PESGM 2017 (pp. 1-5). (IEEE Power and Energy Society General Meeting; Vol. 2018-January). IEEE Computer Society. https://doi.org/10.1109/PESGM.2017.8274057

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title = "Optimal allocation of static var compensator via mixed integer conic programming",

abstract = "Shunt FACTS devices, such as, a Static Var Compensator (SVC), are capable of providing local reactive power compensation. They are widely used in the network to reduce the real power loss and improve the voltage profile. This paper proposes a planning model based on mixed integer conic programming (MICP) to optimally allocate SVCs in the transmission network considering load uncertainty. The load uncertainties are represented by a number of scenarios. Reformulation and linearization techniques are utilized to transform the original non-convex model into a convex second order cone programming (SOCP) model. Numerical case studies based on the IEEE 30-bus system demonstrate the effectiveness of the proposed planning model.",

keywords = "Load uncertainties, Mixed integer conic programming (MICP), Optimization, SVC allocation, Transmission network",

author = "Xiaohu Zhang and Di Shi and Zhiwei Wang and Junhui Huang and Xu Wang and Guodong Liu and Kevin Tomsovic",

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Zhang, X, Shi, D, Wang, Z, Huang, J, Wang, X, Liu, G & Tomsovic, K 2018, Optimal allocation of static var compensator via mixed integer conic programming. 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, 07/16/17. https://doi.org/10.1109/PESGM.2017.8274057

Optimal allocation of static var compensator via mixed integer conic programming. / Zhang, Xiaohu; Shi, Di; Wang, Zhiwei 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

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AU - Zhang, Xiaohu

AU - Shi, Di

AU - Wang, Zhiwei

AU - Huang, Junhui

AU - Wang, Xu

AU - Liu, Guodong

AU - Tomsovic, Kevin

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N2 - Shunt FACTS devices, such as, a Static Var Compensator (SVC), are capable of providing local reactive power compensation. They are widely used in the network to reduce the real power loss and improve the voltage profile. This paper proposes a planning model based on mixed integer conic programming (MICP) to optimally allocate SVCs in the transmission network considering load uncertainty. The load uncertainties are represented by a number of scenarios. Reformulation and linearization techniques are utilized to transform the original non-convex model into a convex second order cone programming (SOCP) model. Numerical case studies based on the IEEE 30-bus system demonstrate the effectiveness of the proposed planning model.

AB - Shunt FACTS devices, such as, a Static Var Compensator (SVC), are capable of providing local reactive power compensation. They are widely used in the network to reduce the real power loss and improve the voltage profile. This paper proposes a planning model based on mixed integer conic programming (MICP) to optimally allocate SVCs in the transmission network considering load uncertainty. The load uncertainties are represented by a number of scenarios. Reformulation and linearization techniques are utilized to transform the original non-convex model into a convex second order cone programming (SOCP) model. Numerical case studies based on the IEEE 30-bus system demonstrate the effectiveness of the proposed planning model.

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Optimal allocation of static var compensator via mixed integer conic programming

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