A Scenario-based Storage Planning Framework with Probabilistic Guarantees

Chao Yan; Xinbo Geng; Le Xie; Zhaohong Bie

doi:10.1109/iSPEC48194.2019.8975144

A Scenario-based Storage Planning Framework with Probabilistic Guarantees

Chao Yan
, Xinbo Geng
, Le Xie
, Zhaohong Bie

School of Electrical Engineering

Xi'an Jiaotong University
Texas A&M University

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

3 Scopus citations

Abstract

The deepening penetration of renewable energy resources poses critical challenges on the secure and reliable operation of power systems. Energy storage, which could smooth out the fluctuations brought about by the renewables, is one major solution to addressing those challenges. Storage planning, which determines the optimal site and size of the energy storage system, could effectively facilitate the integration of renewables. To consider the impacts of uncertain renewables, this paper proposes a probabilistic framework for storage planning. It explicitly models the operation risk by incorporating individual chance constraints. The chance constraints are converted to deterministic constraints using historical data via the scenario approach. The probabilistic storage planning problem is further decomposed into an upper- level problem and several lower-level problems, and solved via a sub-gradient cutting-plane algorithm. Numerical simulations are conducted on the IEEE 6-bus system.

Original language	English
Title of host publication	iSPEC 2019 - 2019 IEEE Sustainable Power and Energy Conference
Subtitle of host publication	Grid Modernization for Energy Revolution, Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2341-2346
Number of pages	6
ISBN (Electronic)	9781728149301
DOIs	https://doi.org/10.1109/iSPEC48194.2019.8975144
State	Published - Nov 2019
Event	2019 IEEE Sustainable Power and Energy Conference, iSPEC 2019 - Beijing, China Duration: 21 Nov 2019 → 23 Nov 2019

Publication series

Name	iSPEC 2019 - 2019 IEEE Sustainable Power and Energy Conference: Grid Modernization for Energy Revolution, Proceedings

Conference

Conference	2019 IEEE Sustainable Power and Energy Conference, iSPEC 2019
Country/Territory	China
City	Beijing
Period	21/11/19 → 23/11/19

UN SDGs

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

SDG 7 Affordable and Clean Energy

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10.1109/iSPEC48194.2019.8975144

Cite this

Yan, C., Geng, X., Xie, L., & Bie, Z. (2019). A Scenario-based Storage Planning Framework with Probabilistic Guarantees. In iSPEC 2019 - 2019 IEEE Sustainable Power and Energy Conference: Grid Modernization for Energy Revolution, Proceedings (pp. 2341-2346). Article 8975144 (iSPEC 2019 - 2019 IEEE Sustainable Power and Energy Conference: Grid Modernization for Energy Revolution, Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/iSPEC48194.2019.8975144

Yan, Chao ; Geng, Xinbo ; Xie, Le et al. / A Scenario-based Storage Planning Framework with Probabilistic Guarantees. iSPEC 2019 - 2019 IEEE Sustainable Power and Energy Conference: Grid Modernization for Energy Revolution, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 2341-2346 (iSPEC 2019 - 2019 IEEE Sustainable Power and Energy Conference: Grid Modernization for Energy Revolution, Proceedings).

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title = "A Scenario-based Storage Planning Framework with Probabilistic Guarantees",

abstract = "The deepening penetration of renewable energy resources poses critical challenges on the secure and reliable operation of power systems. Energy storage, which could smooth out the fluctuations brought about by the renewables, is one major solution to addressing those challenges. Storage planning, which determines the optimal site and size of the energy storage system, could effectively facilitate the integration of renewables. To consider the impacts of uncertain renewables, this paper proposes a probabilistic framework for storage planning. It explicitly models the operation risk by incorporating individual chance constraints. The chance constraints are converted to deterministic constraints using historical data via the scenario approach. The probabilistic storage planning problem is further decomposed into an upper- level problem and several lower-level problems, and solved via a sub-gradient cutting-plane algorithm. Numerical simulations are conducted on the IEEE 6-bus system.",

author = "Chao Yan and Xinbo Geng and Le Xie and Zhaohong Bie",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE Sustainable Power and Energy Conference, iSPEC 2019 ; Conference date: 21-11-2019 Through 23-11-2019",

year = "2019",

month = nov,

doi = "10.1109/iSPEC48194.2019.8975144",

language = "英语",

series = "iSPEC 2019 - 2019 IEEE Sustainable Power and Energy Conference: Grid Modernization for Energy Revolution, Proceedings",

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Yan, C, Geng, X, Xie, L & Bie, Z 2019, A Scenario-based Storage Planning Framework with Probabilistic Guarantees. in iSPEC 2019 - 2019 IEEE Sustainable Power and Energy Conference: Grid Modernization for Energy Revolution, Proceedings., 8975144, iSPEC 2019 - 2019 IEEE Sustainable Power and Energy Conference: Grid Modernization for Energy Revolution, Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 2341-2346, 2019 IEEE Sustainable Power and Energy Conference, iSPEC 2019, Beijing, China, 21/11/19. https://doi.org/10.1109/iSPEC48194.2019.8975144

A Scenario-based Storage Planning Framework with Probabilistic Guarantees. / Yan, Chao; Geng, Xinbo; Xie, Le et al.
iSPEC 2019 - 2019 IEEE Sustainable Power and Energy Conference: Grid Modernization for Energy Revolution, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. p. 2341-2346 8975144 (iSPEC 2019 - 2019 IEEE Sustainable Power and Energy Conference: Grid Modernization for Energy Revolution, Proceedings).

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

TY - GEN

T1 - A Scenario-based Storage Planning Framework with Probabilistic Guarantees

AU - Yan, Chao

AU - Geng, Xinbo

AU - Xie, Le

AU - Bie, Zhaohong

PY - 2019/11

Y1 - 2019/11

N2 - The deepening penetration of renewable energy resources poses critical challenges on the secure and reliable operation of power systems. Energy storage, which could smooth out the fluctuations brought about by the renewables, is one major solution to addressing those challenges. Storage planning, which determines the optimal site and size of the energy storage system, could effectively facilitate the integration of renewables. To consider the impacts of uncertain renewables, this paper proposes a probabilistic framework for storage planning. It explicitly models the operation risk by incorporating individual chance constraints. The chance constraints are converted to deterministic constraints using historical data via the scenario approach. The probabilistic storage planning problem is further decomposed into an upper- level problem and several lower-level problems, and solved via a sub-gradient cutting-plane algorithm. Numerical simulations are conducted on the IEEE 6-bus system.

AB - The deepening penetration of renewable energy resources poses critical challenges on the secure and reliable operation of power systems. Energy storage, which could smooth out the fluctuations brought about by the renewables, is one major solution to addressing those challenges. Storage planning, which determines the optimal site and size of the energy storage system, could effectively facilitate the integration of renewables. To consider the impacts of uncertain renewables, this paper proposes a probabilistic framework for storage planning. It explicitly models the operation risk by incorporating individual chance constraints. The chance constraints are converted to deterministic constraints using historical data via the scenario approach. The probabilistic storage planning problem is further decomposed into an upper- level problem and several lower-level problems, and solved via a sub-gradient cutting-plane algorithm. Numerical simulations are conducted on the IEEE 6-bus system.

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M3 - 会议稿件

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T3 - iSPEC 2019 - 2019 IEEE Sustainable Power and Energy Conference: Grid Modernization for Energy Revolution, Proceedings

SP - 2341

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BT - iSPEC 2019 - 2019 IEEE Sustainable Power and Energy Conference

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2019 IEEE Sustainable Power and Energy Conference, iSPEC 2019

Y2 - 21 November 2019 through 23 November 2019

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Yan C, Geng X, Xie L, Bie Z. A Scenario-based Storage Planning Framework with Probabilistic Guarantees. In iSPEC 2019 - 2019 IEEE Sustainable Power and Energy Conference: Grid Modernization for Energy Revolution, Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. p. 2341-2346. 8975144. (iSPEC 2019 - 2019 IEEE Sustainable Power and Energy Conference: Grid Modernization for Energy Revolution, Proceedings). doi: 10.1109/iSPEC48194.2019.8975144

A Scenario-based Storage Planning Framework with Probabilistic Guarantees

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