Title :
Distribution Network Fault Restoration Based on Improved Adaptive Genetic Algorithm
Author :
Siqing, Sheng ; Zhigang, Ma ; Jing, Wu ; Nan, Gao
Author_Institution :
Sch. of Electr. & Electr. Eng., North China Electr. Power Univ., Baoding, China
Abstract :
In this paper, the mathematical model of fault restoration is established, and presents a genetic algorithm which includes the heuristic algorithm and adaptive algorithm for solving it. The initial population is generated by the heuristic algorithm, and apply heuristic algorithm to repair the infeasible solution, the algorithm improves the convergence speed effectively. In the process of optimizing, the application of improved adaptive algorithm in the crossover rate and mutation rate speeds up the search rate and avoids premature convergence effectively. In this paper, the example of 33-node distribution system of IEEE shows that the algorithm has high convergence, strong real-time and global stability.
Keywords :
genetic algorithms; power distribution faults; 33-node distribution system; convergence speed; distribution network fault restoration; heuristic algorithm; improved adaptive genetic algorithm; Adaptive algorithm; Computer networks; Convergence; Distributed computing; Genetic algorithms; Heuristic algorithms; Intelligent networks; Mathematical model; Power system restoration; Voltage; adaptive; distribution network; fault restoration; genetic algorithm; heuristic;
Conference_Titel :
Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
Conference_Location :
Changsha, Hunan
Print_ISBN :
978-0-7695-3804-4
DOI :
10.1109/ICICTA.2009.84