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Published on: June 1, 2022
RMP model based optimization of power system stabilizers in multi-machine power system.
Seung-Mook Baek1, Jung-Wook Park
1School of Electrical & Electronic Engineering, YONSEI University, 134 Sinchon-dong, Seodaemun-gu, Seoul, 120-749, Republic of Korea. sm_baek@yonsei.ac.kr
Summary
This study optimizes power system stabilizer (PSS) parameters using the reduced multivariate polynomial (RMP) algorithm. The method enhances low-frequency oscillation damping and system robustness against disturbances.
Area of Science:
- Electrical Engineering
- Control Systems Engineering
- Computational Mathematics
Background:
- Power systems require robust control for stability during large disturbances.
- Traditional methods for tuning power system stabilizers (PSS) may not fully address nonlinear dynamics.
- Optimizing PSS parameters is crucial for effective damping of low-frequency oscillations.
Purpose of the Study:
- To present a novel nonlinear parameter optimization method for PSS using the reduced multivariate polynomial (RMP) algorithm.
- To optimally tune the output saturation limiter of PSS for improved damping performance.
- To evaluate the robustness of the optimized PSS against various disturbances in different power system configurations.
Main Methods:
- Utilizing the reduced multivariate polynomial (RMP) algorithm, which estimates second-order partial derivatives of the Hessian matrix.
- Employing hybrid system modeling with a differential-algebraic-impulsive-switched (DAIS) structure to compute trajectory sensitivities.
- Optimizing PSS nonlinear parameters by minimizing an objective function (OF) representing desired performance measures.
- Performing time-domain simulations on single-machine infinite bus (SMIB) and multi-machine power system (MMPS) test cases.
Main Results:
- The RMP algorithm effectively optimizes nonlinear PSS parameters, including the output saturation limiter.
- Demonstrated significant improvement in low-frequency oscillation damping performance during large disturbances.
- Achieved robust performance of multiple PSSs on the IEEE benchmark two-area four-machine power system against various disturbances.
- Validated the proposed method through comprehensive case studies on SMIB and MMPS.
Conclusions:
- The RMP algorithm offers an efficient and effective approach for nonlinear parameter optimization of PSS.
- The optimized PSS demonstrates enhanced damping capabilities and robustness in power systems.
- The method provides a valuable tool for improving the stability and performance of modern power grids.
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