This paper discusses the use of a stochastic metaheuristic population-based optimization algorithm known as the sine cosine algorithm (SCA) to design the parameters of a power system stabilizer (PSS) for damping electromechanical oscillations in a single machine connected to a large power system. The design of the PSS parameters was formulated as an optimization problem to minimize the objective function value. The SCA was used to obtain the best values of the PSS parameters under the objective function. Simulation was carried out by a linearized power system model. The lead lag controller was used as the PSS structure and the results from that were compared with those obtained by moth flame optimization and evolutionary programming. The results showed that the SCA is more effective than are the other techniques in exploration and exploitation to tune the PSS parameters and enhance the power system stability by damping oscillations in a range of loading conditions.