L'optimisation du stockage de la batterie avec pyomo

Je suis en train d'essayer d'optimiser les Émissions de CO2 de househould basé sur la consommation d'électricité. Il comprend également une batterie de stockage. Mais pour une raison quelconque, l'état de l'énergie de calcul ne fonctionne pas. Je reçois cette erreur:

WARNING: Implicitly replacing the Component attribute soe (type=<class
    'pyomo.core.base.var.IndexedVar'>) on block unknown with a new Component
    (type=<class 'pyomo.core.base.constraint.IndexedConstraint'>). This is
    usually indicative of a modelling error. To avoid this warning, use
    block.del_component() and block.add_component().

Restarting kernel...

C'est mon code pour l'instant:

model = ConcreteModel()

n = 30
model.t = RangeSet(1, n)

model.consumption = Param(model.t, initialize = df['Consumption'])
model.pv = Param(model.t, initialize = df['PV'])
model.emissionen = Param(model.t, initialize = df['CO2-Emissions'])
model.heatpump = Param(model.t, initialize = df['Heatpump'])

in_out_leistung = bt.iloc[1]['Values']
in_out_efficiency = bt.iloc[2]['Values']
battery_capacity = bt.iloc[0]['Values'] 
soe_start = 0
elec_import_max = 200

model.soe = Var(model.t, initialize = 0, within = NonNegativeReals)
model.charge = Var(model.t, within = NonNegativeReals, initialize = 0)
model.discharge = Var(model.t, within = NonNegativeReals, initialize = 0)
model.elec_grid = Var(model.t, bounds = (0, elec_import_max), within = NonNegativeReals)

def discharge_capacity_rule(model, t):
    return model.discharge[t] <= in_out_leistung
model.discharge_capacity_rule = Constraint(model.t, rule = discharge_capacity_rule)

def charge_capacity_rule(model, t):
    return model.charge[t] <= in_out_leistung
model.charge_capacity_rule = Constraint(model.t, rule = charge_capacity_rule)
    
def max_capacity_rule(model, t):
    return model.soe[t] <= battery_capacity
model.max_capacity_rule = Constraint(model.t, rule = max_capacity_rule)
    
def soe_start_rule(model):
    return model.soe[1] == soe_start 
model.soe_start_rule = Constraint(rule = soe_start_rule)

def soe(model, t):
    if t == 1:
        return model.soe[t] == soe_start
    else:
        return model.soe[t] == model.soe[t-1] + (model.charge[t] * in_out_efficiency) - model.discharge[t] / in_out_efficiency
model.soe = Constraint(model.t, rule = soe)

def soe_end_rule(model):
    return model.soe[n] == model.soe[1]
model.soe_end_rule = Constraint(rule = soe_end_rule)

def demand(model, t):
    return model.demand[t] == model.heatpump[t] + model.consumption[t] + model.charge[t]
model.demand = Constraint(model.t, rule = demand)

def lastdeckung(model, t):
    return model.pv[t] + model.elec_grid[t] + model.discharge[t] == model.demand[t]
model.lastdeckung = Constraint(model.t, rule = lastdeckung)

def emissionsreduzierung(model, t):
    return sum(model.elec_grid[t] * model.emissionen[t] for t in model.n)
model.emissionsreduzierung = Objective(rule = emissionsreduzierung, sense = minimize)

Le stockage de l'ist censé être vide au début et à la fin aswell.