给我生成一下python代码求解无功优化的代码

在Python中，你可以使用`PuLP`库来构建线性或整数规划模型解决无功优化问题。这里是一个基本的例子，假设我们有一个简单的电力系统模型，只考虑了无功功率平衡和电压限值约束：

from pulp import *

# 创建线性规划模型
model = LpProblem("Unbalanced Power Flow", LpMinimize)

# 定义决策变量（发电机和负荷的无功）
gens = ["Gen_{}".format(i) for i in range(1, 5)]
loads = ["Load_{}".format(i) for i in range(1, 5)]
Q_vars = {gen: LpVariable(gen, lowBound=-float('inf'), upBound=float('inf')) for gen in gens}
Q_loads = {load: LpVariable(load, lowBound=0, upBound=float('inf')) for load in loads}

# 添加目标函数（最小化无功损耗）
objective = lpSum([c1[i] * Q_vars[gens[i]] for i in range(len(gens))])  # 假设c1是损失系数
model += objective

# 添加无功平衡约束
for i in gens:
    model += Q_vars[i] - Q_loads["Load_" + str(i)] == 0

# 添加电压限值约束
V_min, V_max = 0.9, 1.1  # 举例来说，限制在90%到110%标称电压
for node in gens + loads:
    model += V_min <= abs(Q_vars[node]) <= V_max

# 求解
model.solve()

# 输出结果
for var in Q_vars.values():
    print(f"{var.name}: {value(var)}")

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