Growing wind generation in small isolated power systems displaces synchronous diesel units, lowers the rotating inertia and injects a continuous stochastic disturbance into the generation–demand balance, so that the frequency becomes highly sensitive to wind gusts and the fixed-gain proportional–integral (PI) diesel governor struggles to keep it inside the regulatory band. Responsive charging of electric vehicles (EVs) has been proposed as a demand-side resource that can modulate its consumption according to the locally measured frequency, and earlier work on the wind–diesel system of San Cristóbal Island (Galápagos) showed that proportional, soft and aggressive EV strategies using less than 2.5 % of the demand substantially improve the frequency, while retaining the PI governor. This thesis extends that work by replacing the PI governor of the diesel generation with a Mamdani-type fuzzy logic controller (FLC). The controller uses the frequency deviation and its rate of change as inputs, seven triangular membership functions per variable, a 49-rule base, min–max inference and centroid defuzzification, and is arranged in an incremental (PI-type) structure with an additional proportional path so that zero steady-state error is preserved. The complete system — a 3 × 813 kVA diesel plant, a wind farm of three 800 kW doubly-fed induction generators driven by measured high-resolution wind records, induction-motor, constant-impedance and constant-power loads, and a 50 kW controllable EV charging aggregate — is modelled in MATLAB/Simulink. Thirty-two 600 s wind-profile cases (four wind profiles, four EV strategies, two governors) and three transient events are simulated, and compared through extreme frequencies, standard deviation, time within 60 ± 0.15 Hz, settling time and integral absolute error. The simulation results show that the fuzzy governor reduces the standard deviation of frequency by 54–74 % with respect to the PI governor for every wind profile and EV strategy. For the most demanding profile (high wind speed, high turbulence) the fraction of time inside the acceptable band rises from 27.4 % to 56.8 % without EV participation and from 56.4 % to 75.5 % with aggressive EV control. After the loss of two wind turbines the frequency nadir improves from 58.64 Hz to 59.38 Hz, and the peak deviation after a 100 kW load step is reduced by about 60 %. The improvement is maintained when the system inertia, engine dead time and load damping are varied. Combining a fuzzy governor with low-cost EV demand response is thus an effective route to secure frequency control in isolated grids with high wind penetration.
Keywords : frequency control, fuzzy logic controller, electric vehicles, demand response, isolated power system, wind power, diesel generator, MATLAB/Simulink.
Author : YERRAJERLA SUNITHA,MRS. U. LAKSHMI
Title : FUZZY LOGIC BASED EV CHARGING CONTROL FOR FREQUENCY REGULATION IN WIND-DIESEL ISLANDED POWER SYSTEMS
Volume/Issue : 2026;03(11)
Page No : 13-25
