title: RMP model based optimization of power system stabilizers in multi-machine power system.
abstract: This paper describes the nonlinear parameter optimization of power system stabilizer (PSS) by using the reduced multivariate polynomial (RMP) algorithm with the one-shot property. The RMP model estimates the second-order partial derivatives of the Hessian matrix after identifying the trajectory sensitivities, which can be computed from the hybrid system modeling with a set of differential-algebraic-impulsive-switched (DAIS) structure for a power system. Then, any nonlinear controller in the power system can be optimized by achieving a desired performance measure, mathematically represented by an objective function (OF). In this paper, the output saturation limiter of the PSS, which is used to improve low-frequency oscillation damping performance during a large disturbance, is optimally tuned exploiting the Hessian estimated by the RMP model. Its performances are evaluated with several case studies on both single-machine infinite bus (SMIB) and multi-machine power system (MMPS) by time-domain simulation. In particular, all nonlinear parameters of multiple PSSs on IEEE benchmark two-area four-machine power system are optimized to be robust against various disturbances by using the weighted sum of the OFs.
authors: School of Electrical & Electronic Engineering, YONSEI University, 134 Sinchon-dong, Seodaemun-gu, Seoul, 120-749, Republic of Korea. sm_baek@yonsei.ac.kr
authors: Seung-Mook
authors: SM
authors: Baek
authors: Jung-Wook
authors: JW
authors: Park
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D015233:Models, Statistical; D015999:Multivariate Analysis; D017711:Nonlinear Dynamics; D010507:Periodicity; D011210:Power Plants / Q000295:instrumentation*; D013997:Time Factors