Hierarchical Decentralized Network Reconfiguration for Smart Distribution Systems-Part I: Problem Formulation and Algorithm Development

This paper presents a hierarchical decentralized agent-based network reconfiguration methodology to minimize power losses for smart distribution systems. A novel formulation of the network reconfiguration problem is given in which the switch states are the decision variables, and a single-loop branc...

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Veröffentlicht in:IEEE transactions on power systems Jg. 30; H. 2; S. 734 - 743
Hauptverfasser: Fei Ding, Loparo, Kenneth A.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.03.2015
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Decentralized
Decentralized network reconfiguration
Decomposition
distribution system
Formulations
Generators
Heuristic
Heuristic algorithms
heuristic method
hierarchical
intelligent agents
Joining processes
Linear programming
Networks
Optimization
power loss minimization
Reconfiguration
Switches
Switching theory
ISSN:0885-8950, 1558-0679
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Zusammenfassung:This paper presents a hierarchical decentralized agent-based network reconfiguration methodology to minimize power losses for smart distribution systems. A novel formulation of the network reconfiguration problem is given in which the switch states are the decision variables, and a single-loop branch-exchange heuristic algorithm is used to solve the optimization problem. The entire distribution system is decomposed into subsystems based on the connectivity of areas, and an individual agent is assigned to each decomposed subsystem. A two-stage method is defined for coordinating the reconfigurations of decomposed subsystems. The optimal configuration of the entire system results from collaborations of individual agents, and the decentralized approach significantly reduces the computation time. A 118-bus distribution system is used as the example to illustrate the implementation of the method. The development of a demonstration system and more detailed simulation studies are given in Part II to further illustrate the application of the proposed decentralized approach.
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ISSN:0885-8950
1558-0679
DOI:10.1109/TPWRS.2014.2337260