Path-based distribution network modeling: application to reconfiguration for loss reduction
This paper is devoted to efficiently modeling the connectivity of distribution networks, which are structurally meshed but radially operated. A new approach, based on the "path-to-node" concept, is presented, allowing both topological and electrical constraints to be algebraically formulat...
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| Veröffentlicht in: | IEEE transactions on power systems 2005-05, Vol.20 (2), p.556-564 |
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| container_title | IEEE transactions on power systems |
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| creator | Ramos, E.R. Exposito, A.G. Santos, J.R. Iborra, F.L. |
| description | This paper is devoted to efficiently modeling the connectivity of distribution networks, which are structurally meshed but radially operated. A new approach, based on the "path-to-node" concept, is presented, allowing both topological and electrical constraints to be algebraically formulated before the actual radial configuration is determined. In order to illustrate the possibilities of the proposed framework, the problem of network reconfiguration for power loss reduction is considered. Two different optimization algorithms-one resorting to a genetic algorithm and the other solving a conventional mixed-integer linear problem-are fully developed. The validity and effectiveness of the path-based distribution network modeling are demonstrated on different test systems. |
| doi_str_mv | 10.1109/TPWRS.2005.846212 |
| format | Article |
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A new approach, based on the "path-to-node" concept, is presented, allowing both topological and electrical constraints to be algebraically formulated before the actual radial configuration is determined. In order to illustrate the possibilities of the proposed framework, the problem of network reconfiguration for power loss reduction is considered. Two different optimization algorithms-one resorting to a genetic algorithm and the other solving a conventional mixed-integer linear problem-are fully developed. 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A new approach, based on the "path-to-node" concept, is presented, allowing both topological and electrical constraints to be algebraically formulated before the actual radial configuration is determined. In order to illustrate the possibilities of the proposed framework, the problem of network reconfiguration for power loss reduction is considered. Two different optimization algorithms-one resorting to a genetic algorithm and the other solving a conventional mixed-integer linear problem-are fully developed. The validity and effectiveness of the path-based distribution network modeling are demonstrated on different test systems.</description><subject>Algebra</subject><subject>Algorithms</subject><subject>Artificial intelligence</subject><subject>Artificial neural networks</subject><subject>Cost function</subject><subject>Distribution networks</subject><subject>Electric power generation</subject><subject>Fuzzy logic</subject><subject>genetic algorithm</subject><subject>Genetic algorithms</subject><subject>loss minimization</subject><subject>Minimization methods</subject><subject>network reconfiguration</subject><subject>Networks</subject><subject>Optimization</subject><subject>Power loss</subject><subject>Power system modeling</subject><subject>Reconfiguration</subject><subject>Reduction</subject><subject>Simulated annealing</subject><subject>Substations</subject><subject>System testing</subject><issn>0885-8950</issn><issn>1558-0679</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNp9kc1LxDAQxYMouK7-AeKleNBT1yRt0ok3WfyCBRdd8OAh9GO6Zu02a9Ii_vdmrSB48DTDvN8beDxCjhmdMEbVxWL-_Pg04ZSKCaSSM75DRkwIiKnM1C4ZUQARgxJ0nxx4v6KUyiCMyMs8717jIvdYRZXxnTNF3xnbRi12H9a9RWtbYWPa5WWUbzaNKfNvtbORw9K2tVn2bjjV1kWN9T4IVV9uT4dkr84bj0c_c0wWN9eL6V08e7i9n17N4jLlrItrKEoQaVJADrzOBFZJhcjKTHEVllRVNS9QglBSQJUVBeWYAas5Y4AJT8bkfHi7cfa9R9_ptfElNk3eou29BiWZVDyRgTz7l-RAM5VICODpH3Ble9eGEBqkopBSlgWIDVDpQmyHtd44s87dp2ZUb0vR36XobSl6KCV4TgaPQcRfPuVCpCL5Akktih8</recordid><startdate>20050501</startdate><enddate>20050501</enddate><creator>Ramos, E.R.</creator><creator>Exposito, A.G.</creator><creator>Santos, J.R.</creator><creator>Iborra, F.L.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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| source | IEEE Electronic Library (IEL) |
| subjects | Algebra Algorithms Artificial intelligence Artificial neural networks Cost function Distribution networks Electric power generation Fuzzy logic genetic algorithm Genetic algorithms loss minimization Minimization methods network reconfiguration Networks Optimization Power loss Power system modeling Reconfiguration Reduction Simulated annealing Substations System testing |
| title | Path-based distribution network modeling: application to reconfiguration for loss reduction |
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