Reconfigurations of Distribution Networks by Using Ant Colony Algorithms with Improved Directional Selection Schemes

碩士 === 國立清華大學 === 電機工程學系 === 103 === In this thesis, an ant colony algorithm based on directional selection is proposed to solve the problem of distribution network reconfigurations. On the basis of ant colony optimization algorithms, the search direction is based on the direction information...

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Bibliographic Details
Main Authors: He, Liu, 何柳
Other Authors: Chu, Chia Chi
Format: Others
Language:en_US
Published: 2015
Online Access:http://ndltd.ncl.edu.tw/handle/77600184586458564454
Description
Summary:碩士 === 國立清華大學 === 電機工程學系 === 103 === In this thesis, an ant colony algorithm based on directional selection is proposed to solve the problem of distribution network reconfigurations. On the basis of ant colony optimization algorithms, the search direction is based on the direction information which can reduce the probability of previously searched paths. It will be chosen when the searching on the neighborhood. During the exploration process, it breaks the characteristics random down to any cities, but to move according to the pheromone. Thus, this method can avoid the rapid move to the individual best position and the appearance of premature convergence in the vicinity of the wandering. The optimization objective for network configurations includes three items: (i) the minimum network loss, (ii) the optimal load balancing, and (iii) the least switching operations. The voltage overload current is deviated to the penalty function, reducing the constraint conditions. The IEEE33 distribution network example is used for verification. The network after this reconfiguration can still remain stable underload fluctuations. It can be concluded that the change of load does not affect the optimal network structure result. This result also demonstrates that the directional selection ant colony optimization algorithm is independent of the initial configuration of the distribution network. Numerical experiments reflect that the algorithm provides a suitable solution in terms of stability. Finally, by changing the objective weights and penalty factors, groups of switch off position are analyzed A reduction in calculation time can be observed on the 69-node testing network without sacrificing the solution quality.