Optimal control design for power system stabilizer using a novel crow search algorithm dynamic approach

This paper proposes the first application of a novel improved metaheuristic optimization technique, dynamic crow search algorithm (DCSA) to find the optimal design of the power system stabilizer (PSS). Using the novel DCSA adaptive approach provides a global search capability as well as fastness and effectiveness to get the PSS best parameters under the search space constraints and local optimums. Moreover, PSS parameters has a crucial effect on power system stability that is a major nowadays engineering concern, where its best parameters could make a difference by damping small-signal stability oscillations effectively and in the smallest amount of time if they are obtained through a robust algorithm. As a result, PSS will prevent large types of instabilities which could reach up to some generation stations shedding. The novel proposed algorithm is for first time used and tested under different power system instabilities scenarios by using single-machine infinity bus model over multiple operating conditions to damp out perturbation signals effectively by means of getting optimal PSS design parameters, where Integral absolute error (IAE) performance index is used as an objective function to be minimized. Additionally, results obtained by the proposed approach are compared with those obtained by other methods. It is observed that the proposed method has better convergence characteristics and robustness compared to the original version and other comparison methods. It is revealed that the proposed adaptive method is able to improve the power system stability dynamics and damp out perturbation oscillations successfully.