使用Pyomo优化家庭电池储能时SOE计算报错如何解决

修复方案 #

核心错误原因 #

你的报错由变量与约束重名覆盖导致：你先将model.soe定义为储能能量状态的索引变量，后续写SOE时序平衡约束时，又用了model.soe作为约束名称，直接覆盖了原有变量，导致后续所有调用model.soe的逻辑失效，触发内核重启。

其他需要同步修正的问题 #

• 冗余的初始SOE约束：你已经在时序平衡规则中给t=1的场景设置了初始值等于soe_start，不需要再单独定义soe_start_rule重复约束
• 未定义的demand变量：你没有提前声明model.demand变量就直接在约束中调用，会触发变量不存在报错
• 目标函数遍历集合错误：目标函数中你遍历了不存在的model.n属性，正确的遍历对象是你定义的时间集合model.t

修正后完整代码 #

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

# 变量定义
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)

# 充放电功率上限约束
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)

# 储能容量上限约束
def max_capacity_rule(model, t):
    return model.soe[t] <= battery_capacity
model.max_capacity_rule = Constraint(model.t, rule = max_capacity_rule)

# SOE时序平衡约束：改名避免和变量重名
def soe_balance_rule(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_balance_rule = Constraint(model.t, rule = soe_balance_rule)

# 周期末SOE等于0，满足首尾为空要求
def soe_end_rule(model):
    return model.soe[n] == 0
model.soe_end_rule = Constraint(rule = soe_end_rule)

# 功率平衡约束：直接合并需求侧计算，无需额外定义demand变量
def lastdeckung_rule(model, t):
    return model.pv[t] + model.elec_grid[t] + model.discharge[t] == model.heatpump[t] + model.consumption[t] + model.charge[t]
model.lastdeckung_rule = Constraint(model.t, rule = lastdeckung_rule)

# 目标函数：修正遍历集合为model.t
def emissionsreduzierung_rule(model):
    return sum(model.elec_grid[t] * model.emissionen[t] for t in model.t)
model.emissionsreduzierung = Objective(rule = emissionsreduzierung_rule, sense = minimize)

内容的提问来源于stack exchange，提问作者saschav