...
首页> 外文期刊>Smart Grid, IEEE Transactions on >Distributed Frequency Control in Smart Grids via Randomized Demand Response
【24h】

Distributed Frequency Control in Smart Grids via Randomized Demand Response

机译:通过随机需求响应在智能电网中进行分布式频率控制

获取原文
获取原文并翻译 | 示例
           

摘要

Frequency control is essential to maintain the stability and reliability of power grids. For decades, generation side controllers, e.g., governors and automatic generation controllers, have been used to stabilize the frequency of power systems, which incur high operational costs. In smart grids, utilizing demand response is an appealing alternative to control the system frequency at the demand side, which can reduce the dependency of grids on expensive generation side controllers. Despite of economic advantages, the frequency oscillation problem, which occurs when smart appliances simultaneously respond to the system frequency by varying their power consumptions, is the main barrier to realize demand response enabled frequency control in practice. In this paper, we investigate a new distributed control algorithm by randomizing smart appliances' responses to solve this problem. We provide a comprehensive analysis to characterize various impacts of the randomized demand response on the system frequency in terms of its mean and variance over time. Furthermore, based on the frequency dynamics analysis, we determine the average frequency recovery time, the average number of responded smart appliances, and the probability of frequency overshoot, which provide important guidelines for designing our control algorithm. Finally, we validate our analysis via simulations under practical setups.
机译:频率控制对于维持电网的稳定性和可靠性至关重要。数十年来,发电侧控制器(例如,调速器和自动发电控制器)已被用于稳定电力系统的频率,这导致高运营成本。在智能电网中,利用需求响应是在需求侧控制系统频率的一种有吸引力的选择,它可以减少电网对昂贵的发电侧控制器的依赖性。尽管具有经济上的优势,但当智能电器通过改变其功耗同时对系统频率进行响应时,仍会发生频率振荡问题,这实际上是实现启用需求响应的频率控制的主要障碍。在本文中,我们通过随机化智能设备的响应来研究一种新的分布式控制算法来解决此问题。我们提供全面的分析,以根据随机需求响应随时间的均值和方差来表征系统频率的各种影响。此外,基于频率动力学分析,我们确定平均频率恢复时间,响应的智能设备的平均数量以及频率超调的可能性,这为设计控制算法提供了重要指导。最后,我们通过在实际设置下的仿真来验证我们的分析。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号