智能电网大规模部署自动化能耗调度系统的挑战与机遇

H. Akhavan-Hejazi, Zahra Baharlouei, Hamed Mohsenian Rad
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引用次数: 6

摘要

最近的研究表明,用户缺乏如何应对时变价格的知识和缺乏有效的家庭自动化系统是充分利用实时定价优势的两大障碍。因此,在过去的几年里,人们对开发自动化能源消耗调度(ECS)设备越来越感兴趣,以不断监测每小时价格并安排用户可控负荷的运行,以最大限度地减少他们的能源消耗。虽然使用ECS设备的先前结果很有希望,但所有先前的工作都局限于ECS设备的小规模部署。例如,在大多数情况下,配备ECS设备的用户被认为是微电网或连接到分站的馈线的一部分。在本文中,我们研究了ECS设备在具有多个总线和发电机的电网中的大规模部署。每辆公交车的电价是根据该公交车的位置边际电价(LMP)设定的。我们表明,ECS设备大规模部署的一个关键挑战是负载同步。然而,我们建议对LMPs使用移动平均平滑机制,可以解决负载同步问题并稳定系统。此外,我们表明,所提出的大规模ECS系统在降低负荷需求的峰均比、最小化总发电成本和降低用户电费方面具有接近最优的性能。
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Challenges and opportunities in large-scale deployment of automated energy consumption scheduling systems in smart grids
Recent studies have shown that the lack of knowledge among users on how to respond to time-varying prices and the lack of effective home automation systems are two major barriers for fully utilizing the advantages of real-time pricing. Therefore, there has been a growing interest over the past few years towards developing automated energy consumption scheduling (ECS) devices to constantly monitor the hourly prices and schedule the operation of users' controllable load to minimize their energy expenditure. While the prior results in using ECS devices are promising, all prior work are limited to small-scale deployment of ECS devices. For example, in most cases, the users that are equipped with the ECS devices are assumed to be part of a microgrid or a feeder connected to a sub-station. In this paper, we rather investigate large-scale deployment of ECS devices in a power grid with several buses and generators. The price of electricity at each bus is set according to the locational marginal price (LMP) at that bus. We show that a key challenge in large-scale deployment of ECS devices is load synchronization. However, we propose to use a moving average smoothing mechanism for LMPs that can fix the load synchronization problem and stabilize the system. Furthermore, we show that the proposed large-scale ECS system has a close to optimal performance in terms of reducing peak-to-average-ratio in load demand, minimizing the total power generation cost, and lowering users' electricity bills.
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