H. Akhavan-Hejazi, Zahra Baharlouei, Hamed Mohsenian Rad
{"title":"智能电网大规模部署自动化能耗调度系统的挑战与机遇","authors":"H. Akhavan-Hejazi, Zahra Baharlouei, Hamed Mohsenian Rad","doi":"10.1109/SmartGridComm.2012.6485995","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":143915,"journal":{"name":"2012 IEEE Third International Conference on Smart Grid Communications (SmartGridComm)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Challenges and opportunities in large-scale deployment of automated energy consumption scheduling systems in smart grids\",\"authors\":\"H. 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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. 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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.