A new synchronized data‐driven‐based comprehensive approach to enhance real‐time situational awareness of power system,International Transactions on Electrical Energy Systems

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A new synchronized data‐driven‐based comprehensive approach to enhance real‐time situational awareness of power system
International Transactions on Electrical Energy Systems ( IF 1.9 ) Pub Date : 2021-03-30 , DOI: 10.1002/2050-7038.12887
Divya Rishi Shrivastava ₁ , Shahbaz Ahmed Siddiqui ₂ , Kusum Verma ₃

Affiliation

Identification of disturbances that pushes the power system towards insecure limits can assist in timely remedial measures to be taken for improving situation awareness. The information about event's signature is primarily available in the form of frequency or voltage signals obtained from phasor measurements units (PMUs) in real‐time. Proper evaluation of power system event characteristics enhances the situational awareness and assists system operator to develop required corrective measures for secure operations. In this paper, a fast and accurate algorithm is proposed to identify, classify and locate the events using minimum synchronized data for enhancing the situational awareness of the system. An index is developed with short window synchronized bus frequency data of 18 cycles to detect an event in the network. For identifying the type of event, the same data length bus voltage magnitude and frequency synchronized measurements are utilized to develop statistical measures based novel indices. A rule‐based inference from event's signature is also developed to validate the usefulness of indices for classification and location identification of the event. These extracted statistical indices are applied as input to the Random Forest Classifier to classify and locate the events in real‐time. The proposed approach captures real‐time synchronized data and is adaptive to system topological changes. The proposed comprehensive approach for situational awareness is applied to standard IEEE 39 Bus test system and IEEE 118 Bus test system. The results highlight the performance of the composite method for event identification, classification and location identification with less computational burden and high accuracy.

中文翻译：

一种新的基于数据的同步同步综合方法，可增强电力系统的实时态势感知

识别将电力系统推向不安全极限的干扰，可以帮助及时采取补救措施，以提高态势感知能力。有关事件签名的信息主要以从相量测量单元（PMU）实时获得的频率或电压信号的形式提供。正确评估电源系统事件特征可增强态势感知能力，并协助系统操作员制定必要的纠正措施，以确保安全运行。本文提出了一种快速，准确的算法，使用最少的同步数据来识别，分类和定位事件，以增强系统的态势感知能力。利用18个周期的短窗口同步总线频率数据来开发索引，以检测网络中的事件。为了识别事件的类型，使用相同的数据长度总线电压幅度和频率同步测量来开发基于统计指标的新颖索引。还开发了基于事件签名的基于规则的推断，以验证索引对事件的分类和位置标识的有用性。这些提取的统计指标将用作“随机森林分类器”的输入，以实时对事件进行分类和定位。所提出的方法可捕获实时同步数据，并适应系统拓扑变化。所提出的全面的态势感知方法已应用于标准IEEE 39总线测试系统和IEEE 118总线测试系统。结果突出显示了用于事件识别的复合方法的性能，

更新日期：2021-05-03

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