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Hi, a good work! I have a question regarding the constraint formulation in LLM_as_optimizer_gpt.py. I see that the load constraint is set as 'generation >= the total demand'. However, usually power system requires a equality constraint so that the system can be balanced. May I ask if there are some issues in imposing a strict equality constraint? def satisfy_load_constraints(thermal_output): if np.sum(thermal_output)>=400: return True else: return False
Thank you!
The text was updated successfully, but these errors were encountered:
Hi, thanks for your question. Based on our observations, equality constraints are more difficult to satisfy compare to inequality constraints for LLM, therefore in this version we haven't consider them. You're right though, generation and demand balance is important in OPF, please stay tuned for our next updates.
Hi, a good work! I have a question regarding the constraint formulation in LLM_as_optimizer_gpt.py. I see that the load constraint is set as 'generation >= the total demand'. However, usually power system requires a equality constraint so that the system can be balanced. May I ask if there are some issues in imposing a strict equality constraint?
def satisfy_load_constraints(thermal_output): if np.sum(thermal_output)>=400: return True else: return False
Thank you!
The text was updated successfully, but these errors were encountered: