Quantitative evaluation of reliability improvement: Case study on a self-healing distribution system

Jiaojiao Dong; Lin Zhu; Paychuda Kritprajun; Yilu Liu; Leon M. Tolbert; Joshua C. Hambrick; Kevin Schneider; Stuart Laval

doi:10.1109/ISGT45199.2020.9087679

Quantitative evaluation of reliability improvement: Case study on a self-healing distribution system

Jiaojiao Dong, Lin Zhu, Paychuda Kritprajun, Yilu Liu, Leon M. Tolbert, Joshua C. Hambrick, Kevin Schneider, Stuart Laval

Energy and Control Systems Security

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

3 Scopus citations

Abstract

In this work, we develop a methodology and tool to quantitatively evaluate the reliability of a self-healing system that considers practical distribution system features such as the distributed energy resources, microgrids, and service restoration strategies. Also, this paper addresses various practical issues when being applied to an actual Duke Energy distribution system, including the design of feasible and practical service restoration strategies that are used to identify the customer interruptions after a fault, and the incorporation of the utility's historical reliability indices that are used to calibrate the failure rate and repair time of distribution system components such as overhead lines and underground cables. This case study demonstrates the effectiveness of the proposed method.

Original language	English
Title of host publication	2020 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728131030
DOIs	https://doi.org/10.1109/ISGT45199.2020.9087679
State	Published - Feb 2020
Event	2020 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2020 - Washington, United States Duration: Feb 17 2020 → Feb 20 2020

Publication series

Name	2020 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2020

Conference

Conference	2020 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2020
Country/Territory	United States
City	Washington
Period	02/17/20 → 02/20/20

Funding

This work was primarily supported by U.S. Department of Energy Grid Modernization Lab Consortium. This work also made use of Engineering Research Center shared facilities supported 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.

Keywords

Distributed energy resources
Distribution automation
Distribution system
Microgrid
Recloser
Reliability
Self-healing system
Service restoration

Access to Document

10.1109/ISGT45199.2020.9087679

Cite this

Dong, J., Zhu, L., Kritprajun, P., Liu, Y., Tolbert, L. M., Hambrick, J. C., Schneider, K., & Laval, S. (2020). Quantitative evaluation of reliability improvement: Case study on a self-healing distribution system. In 2020 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2020 Article 9087679 (2020 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISGT45199.2020.9087679

Dong, Jiaojiao ; Zhu, Lin ; Kritprajun, Paychuda et al. / Quantitative evaluation of reliability improvement : Case study on a self-healing distribution system. 2020 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2020. Institute of Electrical and Electronics Engineers Inc., 2020. (2020 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2020).

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abstract = "In this work, we develop a methodology and tool to quantitatively evaluate the reliability of a self-healing system that considers practical distribution system features such as the distributed energy resources, microgrids, and service restoration strategies. Also, this paper addresses various practical issues when being applied to an actual Duke Energy distribution system, including the design of feasible and practical service restoration strategies that are used to identify the customer interruptions after a fault, and the incorporation of the utility's historical reliability indices that are used to calibrate the failure rate and repair time of distribution system components such as overhead lines and underground cables. This case study demonstrates the effectiveness of the proposed method.",

keywords = "Distributed energy resources, Distribution automation, Distribution system, Microgrid, Recloser, Reliability, Self-healing system, Service restoration",

author = "Jiaojiao Dong and Lin Zhu and Paychuda Kritprajun and Yilu Liu and Tolbert, {Leon M.} and Hambrick, {Joshua C.} and Kevin Schneider and Stuart Laval",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2020 ; Conference date: 17-02-2020 Through 20-02-2020",

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doi = "10.1109/ISGT45199.2020.9087679",

language = "English",

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Dong, J, Zhu, L, Kritprajun, P, Liu, Y, Tolbert, LM, Hambrick, JC, Schneider, K & Laval, S 2020, Quantitative evaluation of reliability improvement: Case study on a self-healing distribution system. in 2020 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2020., 9087679, 2020 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2020, Institute of Electrical and Electronics Engineers Inc., 2020 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2020, Washington, United States, 02/17/20. https://doi.org/10.1109/ISGT45199.2020.9087679

Quantitative evaluation of reliability improvement: Case study on a self-healing distribution system. / Dong, Jiaojiao; Zhu, Lin; Kritprajun, Paychuda et al.
2020 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2020. Institute of Electrical and Electronics Engineers Inc., 2020. 9087679 (2020 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2020).

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

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AU - Dong, Jiaojiao

AU - Zhu, Lin

AU - Kritprajun, Paychuda

AU - Liu, Yilu

AU - Tolbert, Leon M.

AU - Hambrick, Joshua C.

AU - Schneider, Kevin

AU - Laval, Stuart

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AB - In this work, we develop a methodology and tool to quantitatively evaluate the reliability of a self-healing system that considers practical distribution system features such as the distributed energy resources, microgrids, and service restoration strategies. Also, this paper addresses various practical issues when being applied to an actual Duke Energy distribution system, including the design of feasible and practical service restoration strategies that are used to identify the customer interruptions after a fault, and the incorporation of the utility's historical reliability indices that are used to calibrate the failure rate and repair time of distribution system components such as overhead lines and underground cables. This case study demonstrates the effectiveness of the proposed method.

KW - Distributed energy resources

KW - Distribution automation

KW - Distribution system

KW - Microgrid

KW - Recloser

KW - Reliability

KW - Self-healing system

KW - Service restoration

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ER -

Dong J, Zhu L, Kritprajun P, Liu Y, Tolbert LM, Hambrick JC et al. Quantitative evaluation of reliability improvement: Case study on a self-healing distribution system. In 2020 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2020. Institute of Electrical and Electronics Engineers Inc. 2020. 9087679. (2020 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2020). doi: 10.1109/ISGT45199.2020.9087679

Quantitative evaluation of reliability improvement: Case study on a self-healing distribution system

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