Genetic algorithm sampling the solution space selectively depending on difficulty of power distribution network restoration

A new genetic algorithm for multi agent based autonomous power distribution network restoration system is proposed. The state of the art of this study is to realize a new genetic algorithm using selective sampling for improving the restoration performance. A proposed method realizes the selective sampling by a virtual accident selecting algorithm that changes probability of selecting virtual accident area. The virtual accident selecting algorithm consists of weight table and area-value list. The weight table represents a difficulty of restoration in each accident area. The area-value list represents a difficulty of restoration in latest generation, and effects on weight table in next generation. This architecture enables the system to change the probability of changing each virtual accident area autonomously from restoration simulation. The simulation results show the proposed method achieves to improve the performance.