相量
波形
IEC 61850
光伏系统
试验台
实时计算
计算机科学
时域
频域
工程类
电子工程
电气工程
电力系统
功率(物理)
计算机网络
自动化
电压
物理
机械工程
量子力学
计算机视觉
作者
Lulu Guo,Jinan Zhang,Jin Ye,Stephen J. Coshatt,Wen‐Zhan Song
出处
期刊:IEEE Transactions on Smart Grid
[Institute of Electrical and Electronics Engineers]
日期:2021-12-20
卷期号:13 (2): 1582-1597
被引量:12
标识
DOI:10.1109/tsg.2021.3136559
摘要
The internetworking of grid-connected power electronics converters (PECs) in photovoltaic (PV) farms has inevitably expanded the cyber-attack surfaces. This paper presents a comprehensive study on cyber-attack detection and diagnosis for PEC-enabled PV farms via single waveform sensor to distinguish between normal conditions, open-circuit faults, short-circuit faults, and cyber-attacks. To our knowledge, this has not been attempted before. Firstly, we propose frequency-domain magnitude-based residuals to identify short-circuit faults and a time-domain mean current vector-based feature to distinguish open-circuit faults from other threats. These features can fully reflect the specific physical characteristics of PV farms during threat duration. Secondly, unlike micro phasor measurement units ( $\mu $ PMU) and raw electric waveform-based methods, the proposed innovative features can address novel cyber-attacks that are excluded from the training process. Thirdly, an online hardware-in-the-loop (HIL) testbed using the OPAL-RT real-time digital simulator has verified the effectiveness. The monitoring system runs in real-time while using HIL as an operational solar farm and a National Instruments (NI) data acquisition card as the electric waveform sensor at the point of coupling.
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