Research Article
Design and Performance Analysis of a Multi-level Fuzzy-Based Stabilizer to Dampen Low-Frequency Oscillation in Single-Machine Infinite Bus Systems
@INPROCEEDINGS{10.1007/978-3-031-28725-1_16, author={Tenaw Ayew Mezigebu and Belachew Bantyirga Gessesse}, title={Design and Performance Analysis of a Multi-level Fuzzy-Based Stabilizer to Dampen Low-Frequency Oscillation in Single-Machine Infinite Bus Systems}, proceedings={Artificial Intelligence and Digitalization for Sustainable Development. 10th EAI International Conference, ICAST 2022, Bahir Dar, Ethiopia, November 4-6, 2022, Proceedings}, proceedings_a={ICAST}, year={2023}, month={3}, keywords={LFOs Multi-Level Fuzzy Single-Machine System}, doi={10.1007/978-3-031-28725-1_16} }- Tenaw Ayew Mezigebu
Belachew Bantyirga Gessesse
Year: 2023
Design and Performance Analysis of a Multi-level Fuzzy-Based Stabilizer to Dampen Low-Frequency Oscillation in Single-Machine Infinite Bus Systems
ICAST
Springer
DOI: 10.1007/978-3-031-28725-1_16
Abstract
Power systems are frequently viewed as complex, nonlinear, and dynamic systems. This system is constantly subjected to small disturbances that can result in synchronization loss and system failure. To fix this issue, power system stabilizers are applied to generate extra excitation control signals. Conventional power system stabilizer (CPSS) is difficult to track the dynamic nature of the load since stabilizer gains are determined under specific working conditions. In this paper, a multi-level fuzzy-based stabilizer uses the variation of rotor speed and acceleration as an input to mitigate low-frequency oscillations (LFOs) in single-machine infinite bus systems. The system is represented mathematically by the Heffron Philips K-coefficients model. The controller’s performance was investigated for disturbances exposed to inputs of various membership functions, such as a triangular, gaussian, generalized bell, and trapezoidal. Each membership function is compared. For instance, a multi-level fuzzy-based stabilizer with a triangular membership function settled the rotor angle, rotor speed, and electrical torque deviations 29.5%, 5.9%, and 39.7% faster than the gaussian membership function fuzzy-based PSS, respectively. The study’s findings revealed that the triangular membership function performed better than other membership functions.
