Troubleshooting¶

Infeasible Model¶

Problem: Solver reports the model is infeasible.

Solutions:

1. Check that supply can meet demand at all timesteps
2. Verify capacity limits are sufficient
3. Review storage initial/final states

Unbounded Model¶

Problem: Solver reports the model is unbounded.

Solutions:

1. Add upper bounds to all flows
2. Ensure investment parameters have maximum sizes
3. Verify effect coefficients have correct signs

Unexpected Results¶

Debugging Steps:

1. Enable logging:

   from flixopt import CONFIG
   CONFIG.exploring()
   

2. Start with a minimal model and add complexity incrementally

3. Check units are consistent

4. Visualize results to verify energy balances

Slow Solve Times¶

Solutions:

1. Use longer timesteps or aggregate time periods
2. Use Gurobi instead of HiGHS for large models
3. Set solver options:

   solver = fx.solvers.GurobiSolver(
       time_limit_seconds=3600,
       mip_gap=0.01
   )
   

Getting Help¶

If you're stuck:

1. Search GitHub Issues
2. Open a new issue with:
3. Minimal reproducible example
4. flixopt and Python version
5. Full error message