Affiliations: Department of Business Administration, North China Electric Power University, Baoding, China
Note: [] Corresponding author. Tiannan Ma, Department of Business Administration, North China Electric Power University, Baoding 071003, China. E-mail: [email protected]
Abstract: Distribution network structure optimization is the important part of city network planning; it directly affects the reliability and safety of the electric operation. In order to optimize the traditional ant colony algorithm in distribution network structure optimization, this paper proposes a improved algorithm to solve the problems, such as long time calculating, system premature stagnation, invalid searching and so on. Based on traditional ant colony algorithm, this paper improves it by optimizing transition probability and volatile factor. In the design of transition, the gang control will be realized between two parameters α, β and Maximum iterating times Nmax; In the improvement of the volatile factor, the adaptability will be enhanced. Through the verification analysis of specific example, the results show that improved ant colony algorithm, compared with basic ant colony algorithm, increases the ability of global searching and constringency and accelerates the calculation speed of the algorithm. The modified algorithm is feasible and effective.
Keywords: Distribution network structure optimization, power network operation, ant colony algorithm, volatile factor, global searching
