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Tackling the Load Uncertainty Challenges for Energy Consumption Scheduling in Smart Grid

机译：应对智能电网能耗调度中的负载不确定性挑战

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摘要

In this paper, we propose a novel optimization-based real-time residential load management algorithm that takes into account load uncertainty in order to minimize the energy payment for each user. Unlike most existing demand side management algorithms that assume perfect knowledge of users' energy needs, our design only requires knowing some statistical estimates of the future load demand. Moreover, we consider real-time pricing combined with inclining block rate tariffs. In our problem formulation, we take into account different types of constraints on the operation of different appliances such as must-run appliances, controllable appliances that are interruptible, and controllable appliances that are not interruptible. Our design is multi-stage. As the demand information of the appliances is gradually revealed over time, the operation schedule of controllable appliances is updated accordingly. Simulation results confirm that the proposed energy consumption scheduling algorithm can benefit both users, by reducing their energy expenses, and utility companies, by improving the peak-to-average ratio of the aggregate load demand.
机译：在本文中，我们提出了一种新颖的基于优化的实时住宅负荷管理算法，该算法考虑了负荷​​不确定性，以最大程度地减少每个用户的能源支出。与大多数现有的需求侧管理算法假定用户的能源需求完全了解不同，我们的设计只需要知道一些未来负荷需求的统计估计即可。此外，我们考虑将实时定价与逐渐提高的整体费率费率相结合。在我们的问题表述中，我们考虑了对不同设备（例如必须运行的设备，可中断的可控设备和不可中断的可控设备）的操作的不同类型的约束。我们的设计是多阶段的。随着设备的需求信息随着时间的流逝逐渐显示，可控设备的运行时间表也随之更新。仿真结果表明，所提出的能耗调度算法可以通过降低用户的能源消耗使用户受益，并可以通过提高总负荷需求的峰均比使公用事业公司受益。

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