Adding curtailment costs

[Frank Meissner]

Hi, I try to add curtailment costs to the objective but get the error: 

"ValueError: Constant values in objective function not supported."

This is my code:

pot_generation = n.generators_t["p_max_pu"].loc[:,n_obj_generators_wind] * n.generators["p_nom"].loc[n_obj_generators_wind]

act_generation = n.model["Generator-p"].loc[:,n_obj_generators_wind]

curtailment= -(- act_generation + pot_generation)

sum_curtailemnt =curtailment.sum()

n.model.objective + sum_curtailemnt

With pot_generation --> 

Generator wind-2-SouthWest wind-3-Central wind-4-North \ snapshot 2019-01-01 00:00:00 0.840 0.126000 0.039667 2019-01-01 01:00:00 0.970 0.123333 0.045667

act_generation -->

Variable (snapshot: 25, Generator: 5) ------------------------------------- [2019-01-01 00:00:00, wind-2-SouthWest]: Generator-p[2019-01-01 00:00:00, wind-2-SouthWest] ∈ [-inf, inf] [2019-01-01 00:00:00, wind-3-Central]: Generator-p[2019-01-01 00:00:00, wind-3-Central] ∈ [-inf, inf] [2019-01-01 00:00:00, wind-4-North]: Generator-p[2019-01-01 00:00:00, wind-4-North] ∈ [-inf, inf]

curtailment --> 

LinearExpression (snapshot: 25, Generator: 5): ---------------------------------------------- [2019-01-01 00:00:00, wind-2-SouthWest]: +1 Generator-p[2019-01-01 00:00:00, wind-2-SouthWest] - 0.84 [2019-01-01 00:00:00, wind-3-Central]: +1 Generator-p[2019-01-01 00:00:00, wind-3-Central] - 0.126 [2019-01-01 00:00:00, wind-4-North]: +1 Generator-p[2019-01-01 00:00:00, wind-4-North] - 0.03967

sum_curtailemnt -->

LinearExpression ---------------- +1 Generator-p[2019-01-01 00:00:00, wind-2-SouthWest] + 1 Generator-p[2019-01-01 00:00:00, wind-3-Central] + 1 Generator-p[2019-01-01 00:00:00, wind-4-North] - 2958 ..

Does anyone has an idea which mistake I have?

Thanks, Frank

[Frank Meissner]

I have found the solution:  It is not possible to add a constant - in this case the capacitance P_nom (multiplied by P_max_pu) to the objective. 
Therefore, a new variable curtailment c (for wind and pv) is inserted.

The following then applies:

c >= P_max_pu * P_nom + p_generation

And the objective is supplemented by: xyz EUR x c

Maybe it will help someone.

Frank

[Fabian Neumann]

Hi Frank,

Great that you have found a solution that works for you!

Just note that any constant in the objective function will not change the optimal solution, so likely you could have just omitted the constant term in your custom expressions for the objective function.

Best wishes,

Fabian N