Power System Stabilizer Design Using Real-Coded Genetic Algorithm

Small-signal stability is a key element in the studies of dynamic performance of electric power systems. One of the main considerations in stability analysis is the low-frequency oscillations of rotor due to disturbances of which the power system is susceptible to. These oscillations may sustain and grow in magnitude to cause system separation if adequate damping is not provided, especially during using an AVR in the system. To enhance system damping, the generating unit is equipped with a power system stabilizer (PSS). Conventional PSS controllers are widely utilized in industry to damp the low-frequency inertial oscillations experienced due to disturbances. The design of such stabilizer encompasses finding the best settings of PSS parameters which yield the attainable damping response. Several design approaches and techniques have been proposed (i.e. sequential PSS design, H∞ optimization technique, etc.) over the years. A novel genetic-algorithm (GA) based optimization approach to design a robust PSS is presented in this paper. This proposed approach employs optimization of damping factor (𝛔) and damping ratio (𝛇) in parallel with speed deviation based performance index (IAE) optimization, to obtain the best possible time-domain results (minimum settling time, sserror, etc.). The well-known single-machine infinite bus system is used here. Simulation of the linearized system is presented. The system speed response is investigated with and without PSS. Their results are compared and show that the response of the system with PSS sustains its stability during system upsets, which means that the proposed method gives encouraging results compared with traditional methods.