Evaluation of control methods in a wind energy conversion system based on a low-power permanent magnet synchronous generator

Abstract

Relevance: among renewable energy sources, wind energy is one of the fastest-developing sectors. Many regions of Uzbekistan are characterized by low and moderate wind speeds, which complicates the extraction of maximum energy from small-capacity wind installations; under such conditions, the efficiency of the maximum power point tracking (MPPT) system depends directly on the chosen control strategy. In this study, a wind energy conversion system based on a permanent magnet synchronous generator (PMSG) was modeled in MATLAB/Simulink, and proportional-integral (PI), proportional-integral-derivative (PID), and Fuzzy logic controllers were developed for MPPT control and compared under identical operating conditions. The Fuzzy controller was designed as a Mamdani-type system with two inputs (error and its derivative) and 25 linguistic rules. The simulation results allowed the dynamic responses of all three controllers to be compared in terms of rotor speed and electromagnetic torque.

Aim: to model a small-capacity PMSG-based wind energy conversion system in MATLAB/Simulink and to comparatively evaluate the effectiveness of PI, PID, and Fuzzy logic MPPT controllers under identical operating conditions.

Methods: the wind turbine's aerodynamic model was built on the power coefficient C_p (λ, β), and the PMSG was modeled using voltage and torque equations in the rotor-synchronous d-q reference frame. MPPT control was based on the tip-speed-ratio method to compute the reference rotor speed; the resulting speed error was fed to PI, PID, and a two-input, 25-rule Mamdani-type Fuzzy logic controller.

Results: in this study, a small-capacity PMSG-based wind energy conversion system was modeled in MATLAB/Simulink, and a comparative analysis of PI, PID, and Fuzzy MPPT controllers was carried out. When wind speed was stepped from 8,5 m/s to 6 m/s, the system's efficiency was 0.9074 in both regimes, with all controllers performing equally well in steady state. A significant difference emerged in the transient response: the PID controller showed the largest overshoot (15%) and the slowest settling time, while the Fuzzy controller showed the smallest overshoot (3%) — confirming the superiority of fuzzy logic under variable wind conditions.