Anomaly Detection, Classification and Identification Tool (ADCIT)
Anomaly Detection, Classification and Identification Tool (ADCIT)
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异常检测、分类和识别工具 (ADCIT)
DOI：
10.1016/j.simpa.2023.100465
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Asefi S
中科院分区：
文献类型：
--
作者：
Asefi S
异常检测、分类和识别工具（ADCIT）是一个开源的Matlab和Python代码，用于电力系统状态估计中的异常检测、分类和识别。在Matlab中开发的加权最小二乘（WLS）和扩展卡尔曼滤波器（EKF）状态估计器的输出用作在Python中开发的机器学习算法的输入。ADCIT可以解决硬异常情况;例如，当负载在多个节点同时突然改变时，或者当虚假数据注入攻击同时针对多个状态时，它可以检测和分类情况。此外，ADCIT不需要在存在网络拓扑变化的情况下重新训练机器学习算法。在电网能量管理系统中应用ADCIT可以帮助系统运行人员在异常发生时设计适当的对策。
The Anomaly Detection, Classification and Identification Tool (ADCIT) is an open source Matlab and Python code used for detection, classification and identification of anomalies in power system state estimation. Outputs of weighted least squares (WLS) and extended Kalman filter (EKF) state estimators, developed in Matlab, are used as inputs for machine learning algorithms developed in Python. The ADCIT can address hard anomaly cases; for example, it can detect and classify the case when load is abruptly changed at multiple nodes simultaneously, or when false data injection attack targets multiple states at the same time. Additionally, the ADCIT does not require retraining of the machine learning algorithm in the presence of network topology changes. Application of the ADCIT within power grid energy management system can help system operator to design proper countermeasures in case of an anomaly occurrence.
电力教育工具箱 (P.E.T)：用于状态估计的交互式软件包
DOI：
--
发表时间：
2009
期刊：
IEEE Power & Energy Society General Meeting
影响因子：
--
作者：
A. Abur
通讯作者：
A. Abur