Hi Sonam,
Simulating complex systems like the Kundur Two-Area System with induction motor loads can indeed be computationally intensive, especially when linearizing the model at specific operating points. Here are several strategies to improve the simulation speed in Simulink:
1. Optimize the Model Configuration
- Solver Settings: Use a fixed-step solver if possible, as variable-step solvers can be slower for complex models. Adjust the solver type and step size for better performance.
set_param(model, 'Solver', 'ode45'); % Example of setting a solver
set_param(model, 'FixedStep', '1e-3'); % Example of setting fixed step size
- Simulation Mode: Use 'Accelerator' or 'Rapid Accelerator' mode instead of 'Normal' mode.
set_param(model, 'SimulationMode', 'accelerator');
2. Simplify the Model for Linearization
- Reduce Complexity: Simplify the induction motor model by using reduced-order models or approximations if possible.
- Use Linearization Points: Specify linearization points to focus on critical parts of the model and ignore less important dynamics.
3. Use Efficient Blocks
- Replace Blocks: Use more efficient blocks or custom S-functions if standard blocks are too slow.
- Precompute Values: Precompute any constant values or lookup tables to avoid repeated calculations during simulation.
4. Parallel Computing
- Parallel Computing Toolbox: Utilize the Parallel Computing Toolbox to distribute the computation across multiple cores or machines.
parpool('local'); % Start a parallel pool
Conclusion
By optimizing solver settings, simplifying the model, using efficient blocks, leveraging parallel computing, and utilizing tools like the Simulink Control Design toolbox, you can significantly improve the simulation speed of your Kundur Two-Area System with induction motor load. These strategies should help you achieve faster linearization and make your simulations more efficient.
Thank you.
