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Effect of Weighting Constants on the Convergence of the Steepest Descent Algorithm Used for the Design of a Power System Stabilizer

Abstract This paper presents the effect of weighting constants on the conver gence of the optimization algorithm used for the design of a power system stabilizer (PSS). A simple objective function integrating weighting factors and weighting coefficients takes into account all the critical operating conditions. The steepest descent optimization method based on eigenvalue sensitivity is used for the minimization of the objective function. It was found that the choice of the weighting constants (e.g., weighting factors and weighting coefficients) is critical and has a direct impact on the convergence of the optimization algorithm. Moreover, the performance of the optimized PSS (OPSS) depends on the selection of suitable weighting constants. Simulation results show that the selection of suitable weighting constants is not straightforward and that some trial and error is needed to locate them.