首页> 外文OA文献 >State Estimation in Power Distribution Systems Based on Ensemble Kalman Filtering
【2h】

State Estimation in Power Distribution Systems Based on Ensemble Kalman Filtering

机译:基于集合卡尔曼的配电系统状态估计   过滤

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

State estimation in power distribution systems is a key component forincreased reliability and optimal system performance. Well understood intransmission systems, state estimation is now an area of active research indistribution networks. While several snapshot-based approaches have been usedto solve this problem, few solutions have been proposed in a dynamic framework.In this paper, a Past-Aware State Estimation (PASE) method is proposed fordistribution systems that takes previous estimates into account to improve theaccuracy of the current one, using an Ensemble Kalman Filter. Fewer phasormeasurements units (PMU) are needed to achieve the same estimation error targetthan snapshot-based methods. Contrary to current methods, the proposed solutiondoes not embed power flow equations into the estimator. A theoreticalformulation is presented to compute a priori the advantages of the proposedmethod vis-a-vis the state-of-the-art. The proposed approach is validatedconsidering the 33-bus distribution system and using power consumption tracesfrom real households.
机译:配电系统中的状态估计是提高可靠性和优化系统性能的关键组成部分。众所周知的传输系统,状态估计现在是活跃的研究分布网络领域。虽然已经使用了几种基于快照的方法来解决此问题,但在动态框架中却很少提出解决方案。本文针对配电系统提出了一种过去感知状态估计(PASE)方法,该方法考虑了先前的估计以提高准确性。使用Ensemble Kalman滤波器进行分析。与基于快照的方法相比,实现相同的估计误差目标所需的相量测量单位(PMU)更少。与当前的方法相反,所提出的解决方案没有将潮流方程嵌入到估计器中。提出了一种理论公式来先验地比较所提出的方法相对于现有技术的优点。考虑到33总线配电系统并使用实际家庭的电力消耗轨迹,对所提出的方法进行了验证。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

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