A resilient microgrid formation strategy for load restoration considering master-slave distributed generators and topology reconfiguration

•A resilient microgrid-forming model is set up considering master-slave DG operation.•The topology reconfiguration and microgrid-forming are coordinated in the model.•A mixed-integer second-order cone programming is employed to solve the model. Recent severe power outages caused by extreme weather h...

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Vydané v:	Applied energy Ročník 199; s. 205 - 216
Hlavní autori:	Ding, Tao, Lin, Yanling, Bie, Zhaohong, Chen, Chen
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.08.2017
Predmet:	critical load disasters electricity Master-slave control Microgrid Mixed-integer second-order cone programming modernization Resilient distribution network topology Topology reconfiguration weather Master-slave control Topology reconfiguration Resilient distribution network Microgrid Mixed-integer second-order cone programming
ISSN:	0306-2619, 1872-9118
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Abstract	•A resilient microgrid-forming model is set up considering master-slave DG operation.•The topology reconfiguration and microgrid-forming are coordinated in the model.•A mixed-integer second-order cone programming is employed to solve the model. Recent severe power outages caused by extreme weather hazards have highlighted the importance and urgency of improving the resilience of electric distribution grids. Microgrids with various types of distributed generators (DGs) have the potential to enhance the electricity supply continuity and thus facilitate resilient distribution grids under natural disasters. In this paper, a novel load restoration optimization model is proposed to coordinate topology reconfiguration and microgrid formation while satisfying a variety of operational constraints. The proposed method exploits benefits of operational flexibility provided by grid modernization to enable more critical load pickup. Specifically, a mixed-integer second order cone programming is employed to reduce the computational complexity of the proposed optimization with optimality guaranteed. Finally, the effectiveness of the proposed method has been verified on an IEEE 33-bus test case and a modified 615-bus test system.
AbstractList	Recent severe power outages caused by extreme weather hazards have highlighted the importance and urgency of improving the resilience of electric distribution grids. Microgrids with various types of distributed generators (DGs) have the potential to enhance the electricity supply continuity and thus facilitate resilient distribution grids under natural disasters. In this paper, a novel load restoration optimization model is proposed to coordinate topology reconfiguration and microgrid formation while satisfying a variety of operational constraints. The proposed method exploits benefits of operational flexibility provided by grid modernization to enable more critical load pickup. Specifically, a mixed-integer second order cone programming is employed to reduce the computational complexity of the proposed optimization with optimality guaranteed. Finally, the effectiveness of the proposed method has been verified on an IEEE 33-bus test case and a modified 615-bus test system. •A resilient microgrid-forming model is set up considering master-slave DG operation.•The topology reconfiguration and microgrid-forming are coordinated in the model.•A mixed-integer second-order cone programming is employed to solve the model. Recent severe power outages caused by extreme weather hazards have highlighted the importance and urgency of improving the resilience of electric distribution grids. Microgrids with various types of distributed generators (DGs) have the potential to enhance the electricity supply continuity and thus facilitate resilient distribution grids under natural disasters. In this paper, a novel load restoration optimization model is proposed to coordinate topology reconfiguration and microgrid formation while satisfying a variety of operational constraints. The proposed method exploits benefits of operational flexibility provided by grid modernization to enable more critical load pickup. Specifically, a mixed-integer second order cone programming is employed to reduce the computational complexity of the proposed optimization with optimality guaranteed. Finally, the effectiveness of the proposed method has been verified on an IEEE 33-bus test case and a modified 615-bus test system.
Author	Chen, Chen Lin, Yanling Ding, Tao Bie, Zhaohong
Author_xml	– sequence: 1 givenname: Tao surname: Ding fullname: Ding, Tao email: tding15@mail.xjtu.edu.cn organization: State Key Laboratory of Electrical Insulation and Power Equipment, Xi’an Jiaotong University, Xi’an 710049, China – sequence: 2 givenname: Yanling surname: Lin fullname: Lin, Yanling organization: State Key Laboratory of Electrical Insulation and Power Equipment, Xi’an Jiaotong University, Xi’an 710049, China – sequence: 3 givenname: Zhaohong surname: Bie fullname: Bie, Zhaohong organization: State Key Laboratory of Electrical Insulation and Power Equipment, Xi’an Jiaotong University, Xi’an 710049, China – sequence: 4 givenname: Chen surname: Chen fullname: Chen, Chen organization: Energy Systems Division, Argonne National Laboratory, Lemont, IL 60439, USA
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Keywords	Master-slave control Topology reconfiguration Resilient distribution network Microgrid Mixed-integer second-order cone programming
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Snippet	•A resilient microgrid-forming model is set up considering master-slave DG operation.•The topology reconfiguration and microgrid-forming are coordinated in the... Recent severe power outages caused by extreme weather hazards have highlighted the importance and urgency of improving the resilience of electric distribution...
SourceID	proquest crossref elsevier
SourceType	Aggregation Database Enrichment Source Index Database Publisher
StartPage	205
SubjectTerms	critical load disasters electricity Master-slave control Microgrid Mixed-integer second-order cone programming modernization Resilient distribution network topology Topology reconfiguration weather
Title	A resilient microgrid formation strategy for load restoration considering master-slave distributed generators and topology reconfiguration
URI	https://dx.doi.org/10.1016/j.apenergy.2017.05.012 https://www.proquest.com/docview/2000381719
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