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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Published in:	IEEE transactions on power systems Vol. 30; no. 2; pp. 734 - 743
Main Authors:	Fei Ding, Loparo, Kenneth A.
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.03.2015 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	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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Abstract	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.
AbstractList	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.
Author	Loparo, Kenneth A. Fei Ding
Author_xml	– sequence: 1 surname: Fei Ding fullname: Fei Ding email: fei.ding@case.edu organization: Dept. of Electr. Eng. & Comput. Sci., Case Western Reserve Univ., Cleveland, OH, USA – sequence: 2 givenname: Kenneth A. surname: Loparo fullname: Loparo, Kenneth A. email: kenneth.loparo@case.edu organization: Dept. of Electr. Eng. & Comput. Sci., Case Western Reserve Univ., Cleveland, OH, USA
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SubjectTerms	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
Title	Hierarchical Decentralized Network Reconfiguration for Smart Distribution Systems-Part I: Problem Formulation and Algorithm Development
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