An efficient simulated annealing algorithm for network reconfiguration in large-scale distribution systems
This paper presents an efficient algorithm for loss minimization by using an automatic switching operation in large-scale distribution systems. Simulated annealing is particularly well suited for a large combinatorial optimization problem since it can avoid local minima by accepting improvements in...
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| Vydáno v: | IEEE transactions on power delivery Ročník 17; číslo 4; s. 1070 - 1078 |
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| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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New York
IEEE
01.10.2002
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 0885-8977, 1937-4208 |
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| Abstract | This paper presents an efficient algorithm for loss minimization by using an automatic switching operation in large-scale distribution systems. Simulated annealing is particularly well suited for a large combinatorial optimization problem since it can avoid local minima by accepting improvements in cost. However, it often requires a meaningful cooling schedule and a special strategy, which makes use of the property of distribution systems in finding the optimal solution. In this paper, we augment the cost function with the operation condition of distribution systems, improve the perturbation mechanism with system topology, and use the polynomial-time cooling schedule, which is based on the statistical calculation during the search. The validity and effectiveness of the proposed methodology is demonstrated in the Korea Electric Power Corporation's distribution system. |
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| AbstractList | This paper presents an efficient algorithm for loss minimization by using an automatic switching operation in large-scale distribution systems. Simulated annealing is particularly well suited for a large combinatorial optimization problem since it can avoid local minima by accepting improvements in cost. However, it often requires a meaningful cooling schedule and a special strategy, which makes use of the property of distribution systems in finding the optimal solution. In this paper, we augment the cost function with the operation condition of distribution systems, improve the perturbation mechanism with system topology, and use the polynomial-time cooling schedule, which is based on the statistical calculation during the search. The validity and effectiveness of the proposed methodology is demonstrated in the Korea Electric Power Corporation's distribution system. |
| Author | Lee, K.Y. Jae-Chul Kim Jin-O Kim Joong-Rin Shin Young-Jae Jeon |
| Author_xml | – sequence: 1 surname: Young-Jae Jeon fullname: Young-Jae Jeon organization: Dept. of Electr. Eng., Soongsil Univ., Seoul, South Korea – sequence: 2 surname: Jae-Chul Kim fullname: Jae-Chul Kim organization: Dept. of Electr. Eng., Soongsil Univ., Seoul, South Korea – sequence: 3 surname: Jin-O Kim fullname: Jin-O Kim – sequence: 4 surname: Joong-Rin Shin fullname: Joong-Rin Shin – sequence: 5 givenname: K.Y. surname: Lee fullname: Lee, K.Y. |
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| SubjectTerms | Algorithms Combinatorial analysis Computational modeling Cooling Cooling systems Cost function Genetic algorithms Intelligent networks Large-scale systems Minimization methods Optimization Schedules Scheduling Searching Simulated annealing Switches |
| Title | An efficient simulated annealing algorithm for network reconfiguration in large-scale distribution systems |
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