I setup a constraint that does not constraint the solver in pyomo.
The constraint is the following:
def revenue_positive(model,t):
for t in model.T:
return (model.D[t] * model.P[t]) >= 0
model.positive_revenue = Constraint(model.T, rule=revenue_positive)
while the model parameters are:
model = ConcreteModel()
model.T = Set(doc='quarter of year', initialize=df.index.tolist(), ordered=True)
model.P = Param(model.T, initialize=df['price'].to_dict(), within=Any, doc='Price for each quarter')
model.C = Var(model.T, domain=NonNegativeReals)
model.D = Var(model.T, domain=NonNegativeReals)
income = sum(df.loc[t, 'price'] * model.D[t] for t in model.T)
expenses = sum(df.loc[t, 'price'] * model.C[t] for t in model.T)
profit = income - expenses
model.objective = Objective(expr=profit, sense=maximize)
# Solve the model
solver = SolverFactory('cbc')
solver.solve(model)
df dataframe is:
df time_stamp price Status imbalance Difference Situation ... week month hour_of_day day_of_week day_of_year yearly_quarter
quarter ...
0 2021-01-01 00:00:00 64.84 Final 16 -3 Deficit ... 00 1 0 4 1 1
1 2021-01-01 00:15:00 13.96 Final 38 2 Surplus ... 00 1 0 4 1 1
2 2021-01-01 00:30:00 12.40 Final 46 1 Surplus ... 00 1 0 4 1 1
3 2021-01-01 00:45:00 7.70 Final 65 14 Surplus ... 00 1 0 4 1 1
4 2021-01-01 01:00:00 64.25 Final 3 -9 Deficit ... 00 1 1 4 1 1
The objective is to constraint the solver not to accept a negative revenue. As such it does not work as the solver passes 6 negative revenue values through. Looking at the indices with negative revenue, it appears the system chooses to sell at a negative price to buy later at a price even "more" negative, so from an optimization standpoint, it is ok. I would like to check the difference in results if we prohibit the solver to do that. Any input is welcome as after many searches on the web, still not the right way to write it correctly.
I did a pprint() of the constraint that returned:
positive_revenue : Size=35040, Index=T, Active=True
UPDATE following new constraint code:
def revenue_positive(model,t):
return model.D[t] * model.P[t] >= 0
model.positive_revenue = Constraint(model.T, rule=revenue_positive)
Return the following error:
ERROR: Rule failed when generating expression for constraint positive_revenue
with index 283: ValueError: Invalid constraint expression. The constraint
expression resolved to a trivial Boolean (True) instead of a Pyomo object.
Please modify your rule to return Constraint.Feasible instead of True.
Error thrown for Constraint 'positive_revenue[283]'
ERROR: Constructing component 'positive_revenue' from data=None failed:
ValueError: Invalid constraint expression. The constraint expression
resolved to a trivial Boolean (True) instead of a Pyomo object. Please
modify your rule to return Constraint.Feasible instead of True.
Error thrown for Constraint 'positive_revenue[283]'
Traceback (most recent call last):
File "/home/olivier/Desktop/Elia - BESS/run_imbalance.py", line 25, in <module>
results_df = optimize_year(df)
File "/home/olivier/Desktop/Elia - BESS/battery_model_imbalance.py", line 122, in optimize_year
model.positive_revenue = Constraint(model.T, rule=revenue_positive)
File "/home/olivier/anaconda3/lib/python3.9/site-packages/pyomo/core/base/block.py", line 542, in __setattr__
self.add_component(name, val)
File "/home/olivier/anaconda3/lib/python3.9/site-packages/pyomo/core/base/block.py", line 1087, in add_component
val.construct(data)
File "/home/olivier/anaconda3/lib/python3.9/site-packages/pyomo/core/base/constraint.py", line 781, in construct
self._setitem_when_not_present(
File "/home/olivier/anaconda3/lib/python3.9/site-packages/pyomo/core/base/indexed_component.py", line 778, in _setitem_when_not_present
obj.set_value(value)
File "/home/olivier/anaconda3/lib/python3.9/site-packages/pyomo/core/base/constraint.py", line 506, in set_value
raise ValueError(
ValueError: Invalid constraint expression. The constraint expression resolved to a trivial Boolean (True) instead of a Pyomo object. Please modify your rule to return Constraint.Feasible instead of True.
Error thrown for Constraint 'positive_revenue[283]'
So there are 2 issues w/ your constraint. It isn't clear if one is a cut & paste issue or not.
The function call to make the constraint appears to be indented and inside of your function after the return statement, making it unreachable code. Could be just the spacing in your post.
You are incorrectly adding a loop inside of your function. You are passing in the parameter t as a function argument and then you are blowing it away with the for loop, which only executes for the first value of t in T then hits the return statement. Remove the loop. When you use the rule= structure in pyomo it will call the rule for each instance of the set that you are using in the Constraint(xx, rule=) structure.
So I think you should have:
def revenue_positive(model, t):
return model.D[t] * model.P[t] >= 0
model.positive_revenue = Constraint(model.T, rule=revenue_positive)
The error cites the 283rd index. My bet is that price[283] is zero, so you are multiplying by a zero and killing your variable.
You could add a check within the function that checks if the price is zero, and in that case, just return pyo.Constraint.Feasible, which is the trivial return that doesn't influence the model (or crash)