用pyomo优化蓄电池

from pyomo.environ import *

# 创建模型
model = ConcreteModel()

# 定义变量
model.x = Var(within=NonNegativeReals)  # 充电量
model.y = Var(within=NonNegativeReals)  # 放电量

# 定义参数
model.capacity = Param(initialize=100)  # 蓄电池容量
model.charge_efficiency = Param(initialize=0.9)  # 充电效率
model.discharge_efficiency = Param(initialize=0.8)  # 放电效率
model.demand = Param(initialize=50)  # 负载需求

# 定义目标函数
def objective_rule(model):
    return model.charge_efficiency * model.x - model.discharge_efficiency * model.y
model.objective = Objective(rule=objective_rule, sense=maximize)

# 定义约束
def capacity_rule(model):
    return model.x - model.y <= model.capacity
model.capacity_constraint = Constraint(rule=capacity_rule)

def demand_rule(model):
    return model.y >= model.demand
model.demand_constraint = Constraint(rule=demand_rule)

# 求解模型
solver = SolverFactory('glpk')
results = solver.solve(model)

# 输出结果
print(f"最优充电量: {model.x.value}")
print(f"最优放电量: {model.y.value}")