Load frequency control of single area power system in Simulink
Welcome to Learn MATLAB's Basic. In this tutorial, we will delve into the intricacies of load frequency control in an isolated power system. The tutorial walks you through creating a symbolic model in MATLAB, simulating the system, and implementing a proportional-integral-derivative (PID) controller for improved frequency stability.
The isolated power system consists of a governor turbine, a rotating mass (generator load), and a feedback loop for small changes in frequency and angular frequency. The goal is to model this system in MATLAB and implement load frequency control.
Creating a Symbolic Model:
Use the symbolic toolbox in MATLAB to model the system.
Utilize transfer functions for the governor turbine and generator load models.
Introduce a summing block to process small changes in mechanical power supply.
Simulating the Model:
Simulate the system using MATLAB to observe its behavior.
Implement a step input to induce a small change in frequency.
Visualize the simulation results using a scope.
Introduction of PID Controller:
Notice the deviation in frequency and angular frequency.
Introduce a PID controller to minimize the deviation and improve stability.
Connect the PID controller to the system using Simulink.
Tuning the PID Controller:
Tune the PID controller parameters (Kp, Ki, Kd) to optimize the system's response.
Utilize default values or experiment with custom tuning.
Observe the response in Simulink and analyze the error reduction.
Adjusting Simulation Parameters:
Modify simulation time to 100 seconds for a more comprehensive analysis.
Fine-tune PID controller parameters to achieve optimal results.
Observe the system's response over an extended period.
The tutorial concludes with a comprehensive understanding of load frequency control in an isolated power system using MATLAB. The PID controller is employed to minimize frequency deviation, and simulation results are analyzed for stability. Viewers are encouraged to experiment with different parameters to further enhance their understanding of the system's behavior.