LAPSE:2023.21990v1
Published Article

LAPSE:2023.21990v1
A Reliability-Based Network Reconfiguration Model in Distribution System with DGs and ESSs Using Mixed-Integer Programming
March 23, 2023
Abstract
Widely used distribution generations (DGs) and energy storage systems (ESSs) enable a distribution system to have a more flexible fault reconfiguration capability. In order to enhance the service reliability and the benefit of distribution networks with DGs and ESSs, this paper proposes a novel distribution system reconfiguration (DSR) model including DGs and ESSs. Meanwhile, the impact of sectionalizing switches and tie switches on reliability is considered. The concept of “boundary switch” is introduced for quantifying the customer interruption duration. The DSR model is presented to minimize the sum of the customer interruption cost, the operation cost of switches, and the depreciation cost of DGs and ESSs. Furthermore, the proposed model is converted into a mixed-integer linear programming, which can be efficiently solved by commercial solvers. Finally, the validity and efficiency of the proposed DSR model are verified by a modified IEEE 33-bus system and a modified PG&E69-bus network. The obtained results indicate the advantages of DGs and ESSs in reducing outage time, and suggest that the types and locations of SSs have great effects on the resulting benefit of DGs and ESSs.
Widely used distribution generations (DGs) and energy storage systems (ESSs) enable a distribution system to have a more flexible fault reconfiguration capability. In order to enhance the service reliability and the benefit of distribution networks with DGs and ESSs, this paper proposes a novel distribution system reconfiguration (DSR) model including DGs and ESSs. Meanwhile, the impact of sectionalizing switches and tie switches on reliability is considered. The concept of “boundary switch” is introduced for quantifying the customer interruption duration. The DSR model is presented to minimize the sum of the customer interruption cost, the operation cost of switches, and the depreciation cost of DGs and ESSs. Furthermore, the proposed model is converted into a mixed-integer linear programming, which can be efficiently solved by commercial solvers. Finally, the validity and efficiency of the proposed DSR model are verified by a modified IEEE 33-bus system and a modified PG&E69-bus network. The obtained results indicate the advantages of DGs and ESSs in reducing outage time, and suggest that the types and locations of SSs have great effects on the resulting benefit of DGs and ESSs.
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Keywords
customer interruption duration, distribution generation, distribution system reconfiguration, energy storage system, mixed-integer programming, switch
Subject
Suggested Citation
Guo S, Lin J, Zhao Y, Wang L, Wang G, Liu G. A Reliability-Based Network Reconfiguration Model in Distribution System with DGs and ESSs Using Mixed-Integer Programming. (2023). LAPSE:2023.21990v1
Author Affiliations
Guo S: School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China
Lin J: School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China
Zhao Y: Shenzhen Power Supply Co., Ltd., Shenzhen 518001, China
Wang L: School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China [ORCID]
Wang G: School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China
Liu G: Shenzhen Power Supply Co., Ltd., Shenzhen 518001, China
Lin J: School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China
Zhao Y: Shenzhen Power Supply Co., Ltd., Shenzhen 518001, China
Wang L: School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China [ORCID]
Wang G: School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China
Liu G: Shenzhen Power Supply Co., Ltd., Shenzhen 518001, China
Journal Name
Energies
Volume
13
Issue
5
Article Number
E1219
Year
2020
Publication Date
2020-03-06
ISSN
1996-1073
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PII: en13051219, Publication Type: Journal Article
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LAPSE:2023.21990v1
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Mar 23, 2023
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