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Smart Household Electricity Usage Optimization Using MPC and MILP*

机译:使用MPC和MILP * 的智能家居用电优化

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This paper suggests scheduling of electric appliances in a smart household if a Time of Use pricing scheme is applied by the utility company. The algorithms discussed in this paper enable the control and the balancing of the energy consumption to ensure minimal electricity costs of the household. The optimal appliances' schedule and the energy consumption pattern are the results of a two-level optimization strategy. The home appliances are scheduled based on a Mixed Integer Linear Programming approach. If an electric vehicle (EV) is also present in the household, its charging is scheduled to achieve the State of Charge desired by its departure time. The EV battery is also considered as power storage device. The second level is reserved to control the electric heating system with a Model Predictive Controller (MPC) considering the results of the first optimization level as energy constraints. The MPC may use the EV battery as a power source where the Vehicle-to-Home technology is adopted. Moreover, we present an EV scenario to discuss the battery lifetime. Simulation results show the energy balancing along with an optimal electricity cost based on the strategy proposed.
机译:如果公用事业公司采用“使用时间”定价方案,则本文建议在智能家居中调度电器。本文讨论的算法可以实现能耗的控制和平衡,以确保将家庭的电费降至最低。最佳的设备计划和能耗模式是两级优化策略的结果。家用电器是基于混合整数线性规划方法进行调度的。如果家庭中也有电动汽车(EV),则安排其充电时间以达到其出发时间所需的充电状态。 EV电池也被视为电力存储设备。保留第二级别,以使用模型预测控制器(MPC)控制电加热系统,将第一优化级别的结果作为能量约束。 MPC可以将EV电池用作采用车载到家技术的电源。此外,我们提出了一种电动汽车方案,以讨论电池寿命。仿真结果表明,基于所提出的策略,能量平衡以及最优的电力成本。

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