Improved Cuckoo Optimization Algorithm for Excitation Control of Synchronous Generators

In this paper, a new modified Cuckoo optimization algorithm (MCOA) is used for the excitation control of a synchronous generator (SG). The performance of the MCOA is examined and tested on such an engineering application system with cost minimization based on system error between system outputs and reference values. Then, the application of an adapted MCOA, evolutionary-based approach, to design a state feedback controller is proposed; and this is adopted for adjusting and determining the optimal settings of a state controller to cancel the oscillations in synchronous generators. A compression is performed between MCOA and Ant Colony Optimization algorithm (ACO) where the results show that the MCOA-based state feedback controller has obtained good performance as compared to ACO for excitation control of SG through the reduction of the effect of the unwanted low frequencies oscillations.