Multi-object reconfiguration for smart distribution network
The smart distribution system is required to be recovered effectively after the failure occurring. The control algorithm is the key factor. Due to the structure of the radial distribution network, a novel algorithm of reconstruction is presented. First, the calculation method of power flow is a back...
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| Published in | Chinese Control Conference pp. 10056 - 10060 |
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| Main Authors | , , , |
| Format | Conference Proceeding Journal Article |
| Language | English |
| Published |
TCCT
01.07.2016
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1934-1768 |
| DOI | 10.1109/ChiCC.2016.7554947 |
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| Summary: | The smart distribution system is required to be recovered effectively after the failure occurring. The control algorithm is the key factor. Due to the structure of the radial distribution network, a novel algorithm of reconstruction is presented. First, the calculation method of power flow is a back-forward sweep method based on layered node. Furthermore, a quantum genetic algorithm is proposed for the reconfiguration of the distribution network for multi-object. The quantum genetic algorithm utilizes the quantum bit to encode chromosome and uses the quantum rotation gate to achieve the adjustment of the chromosome. It has the advantage of rapid convergence to the global optimal solution, and overcomes the shortcoming of the genetic algorithm with large calculation burden. The multi-objective target is taken as the combination of the power loss of the distribution network and the number of switches operations. In this paper, the simulation and analysis of an IEEE 16 nodes system are carried out using MATLAB programming. The results demonstrate that the scheme finds out the optimal reconfiguration scheme more quickly comparing with the traditional genetic algorithm, and verifies the effectiveness of the proposed method. |
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| Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Conference-1 ObjectType-Feature-3 content type line 23 SourceType-Conference Papers & Proceedings-2 |
| ISSN: | 1934-1768 |
| DOI: | 10.1109/ChiCC.2016.7554947 |