Parameter polyoptimization of PSS2A power system stabilizers operating in a multi-machine power system including the uncertainty of model parameters
We perform parameter polyoptimization of power system stabilizers in a multi-machine power system.We use the genetic algorithm for investigations.In the analysis the parameter uncertainty is included.We use the modified Euclidean measure for estimation of the results. In the paper there is presented the analysis of the results of parameter optimization of the PSS2A power system stabilizers when taking into account the uncertainty of the power system (PS) mathematical model parameters. For parameter optimization of power system stabilizers (PSSs) there was used, among others, multi-criteria optimization (polyoptimization, Pareto optimization). The optimization criteria were determined for a selected disturbance in the multi-machine PS, taking into account the transient waveforms associated with electromechanical swings (waveforms of the instantaneous power and angular speed of a generator) as well as the waveforms of the terminal voltage of synchronous generators. The use of multi-criteria optimization enables taking into account many, sometimes contradictory, requirements (criteria) in the parameter optimization of PSSs without the loss of ability to achieve the optimal solution. A genetic algorithm with floating point encoding, multi-criteria tournament selection, modified simple crossover and non-uniform mutation was used for the optimization. Moreover, there was analyzed the influence of the uncertainty of the PS mathematical model parameters on the results of the parameter optimization of PSSs with the use of the worked out factor based on Euclidean measure.