scholarly journals A Study on Improvement of Tabu Search-based Determination Method for Distribution Network Configuration

2013 ◽  
Vol 3 (1) ◽  
pp. 61-67 ◽  
Author(s):  
Hirotaka Takano ◽  
Junichi Murata ◽  
Makoto Yasuda ◽  
Yukino Maki
Author(s):  
Hirotaka Takano ◽  
◽  
Junichi Murata ◽  
Yukino Maki ◽  
Makoto Yasuda ◽  
...  

The distribution network reconfiguration problem is to decide whether each sectionalizing switch is to be open or closed in order to maintain or improve electrical power supply reliability, power quality and network operation efficiency. Obtaining the optimal network configuration is, however, extremely difficult because the network reconfiguration problem is actually a large-size combinatorial optimization problem. Many optimization algorithms have thus been applied to the reconfiguration problem to support power utility’s decision-making. This paper proposes a local search-based solution for the reconfiguration problem in which tabu search – one of the most widely used local search-based metaheuristics – is employed to solve the problem. Tabu search is improved by introducing an effective search strategy that utilizes the properties of this kind of problems. Numerical simulations are performed on a complex actual-scale distribution network model in order to verify the validity of the proposed solution.


2009 ◽  
Vol 129 (6) ◽  
pp. 733-744 ◽  
Author(s):  
Shoji Kawasaki ◽  
Yasuhiro Hayashi ◽  
Junya Matsuki ◽  
Hirotaka Kikuya ◽  
Masahide Hojo

2018 ◽  
Vol 20 (K7) ◽  
pp. 5-14
Author(s):  
Linh Tung Nguyen ◽  
Thuan Thanh Nguyen ◽  
Trieu Ngoc Ton ◽  
Anh Viet Truong ◽  
Xuan Anh Nguyen

This paper presents a method of determining the location and size of distributed generation (DG) considering to operate the configuration of distribution network to minimize the real power loss. The proposed method which is based on the genetic algorithm (GA) is divided into two stages. In the first stage, GA is used to optimize the location and size of DG in the mesh distribution network, while in the second stage, GA is used to determine the radial network configuration after installing DG. The simulation results on the 33-nodes and 69-nodes systems show that the proposed method can be an efficient method for the placing DG problem and that is considering to solve the problem of distribution network reconfiguration.


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