Power System Small-Signal (Low-Frequency Oscillation) Stability Analysis

Resource Overview

This MATLAB/SIMULINK-based study analyzes small-signal (low-frequency oscillation) stability in simple power systems through four key approaches: 1) Building system simulation models using SIMULINK blocks and parameter configuration 2) Comparative analysis of AVR and PSS impacts on stability using controlled simulation scenarios 3) Root locus plotting for exciter gain KA and PSS gain KSTAB with stability margin evaluation 4) Rotor speed response simulation under 5-step voltage reference changes with/without PSS implementation

Detailed Documentation

This research utilizes MATLAB/SIMULINK to analyze small-signal (low-frequency oscillation) stability in simple power systems through the following methodological framework: 1) System simulation model development using SIMULINK, involving component blocks such as synchronous machines, excitation systems, and power system stabilizers with precise parameter configuration through MATLAB workspace variables and mask parameters. 2) Comparative stability analysis under four scenarios: without AVR/PSS, with AVR only, with PSS only, and with both AVR and PSS. The analysis employs linearization tools like 'linearize' function to extract state-space models and calculate eigenvalues for stability assessment. 3) Root locus plotting for exciter gain KA and PSS gain KSTAB using Control System Toolbox functions (rlocus, sisotool). The analysis involves systematic gain variation and pole movement tracking to determine stability boundaries and damping ratio relationships. 4) Time-domain simulation of rotor speed response under 5-step voltage reference changes using SIMULINK's solver configurations. The comparison between PSS-enabled and PSS-disabled cases demonstrates oscillation damping effectiveness through ode45 solver with variable-step settings. Through this comprehensive approach, the research provides deep insights into small-signal stability characteristics of power systems and quantitatively evaluates how different control elements influence system dynamic behavior.