This paper investigates the scheduling strategy of schedulable load in home energy management system (HEMS) under uncertain environment by proposing a distributionally robust optimization (DRO) method based on receding horizon optimization (RHO-DRO). First, the optimization model of HEMS, which contains uncertain variable outdoor temperature and hot water demand, is established and the scheduling problem is developed into a mixed integer linear programming (MILP) by using the DRO method based on the ambiguity sets of the probability distribution of uncertain variables. Combined with RHO, the MILP is solved in a rolling fashion using the latest update data related to uncertain variables. The simulation results demonstrate that the scheduling results are robust under uncertain environment while satisfying all operating constraints with little violation of user thermal comfort. Furthermore, compared with the robust optimization (RO) method, the RHO-DRO method proposed in this paper has a lower conservation and can save more electricity for users.

中文翻译：

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基于后验优化的家庭能源管理系统分布鲁棒优化

本文提出了一种基于后向视野优化（RHO-DRO）的分布式鲁棒优化（DRO）方法，研究了不确定环境下家庭能源管理系统（HEMS）中可调度负荷的调度策略。首先，建立了包含不确定的变量户外温度和热水需求的HEMS优化模型，并基于概率分布的模糊集，使用DRO方法将调度问题发展为混合整数线性规划（MILP）不确定变量。结合RHO，使用与不确定变量有关的最新更新数据以滚动方式解决MILP。仿真结果表明，在不确定的环境下，调度结果具有较强的鲁棒性，同时满足了所有运行约束，几乎没有违反用户的热舒适性。此外，与鲁棒优化（RO）方法相比，本文提出的RHO-DRO方法具有较低的保护性，可以为用户节省更多的电量。