Parameter Identification of Synchronous Generator by Using Ant Colony Optimization Algorithm

Aiming at the problems of parameter identification of synchronous generator, which needs long time and is easy to get into the local optimization, ant colony optimization (ACO) for parameter identification of synchronous generator in continuous space is proposed. When the problem is defined using ACO algorithm, it combines the advantage of rapidness and global optimization. Simulation results show that it is very effective. An experiment is carried out by the simulative generator whose type is MF-15. A step is added to the field system, and based on the transient behavior of the machine, the electrical parameters are identified by using the method proposed in the paper. Experimental results show that ACO is tit for continuous optimization of synchronous generator, and the method is valid and feasible.