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Online Transfer Function Estimation and Control Design Using Ambient Synchrophasor Measurements

delete2023-01-01
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PRE
AI
M
Mohammadreza Hatami
K
Kasra Koorehdavoudi
H
Habib Wajid
V
V. Venkatasubramanian *
P
Patrick Panciatici
F
Florent Xavier
G
Gilles Torresan
DOI:10.1109/TPWRS.2022.3157251delete
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摘要

摘要

En 中文
This paper proposes an adaptive control design framework for damping inter-area oscillations in power systems. The design is entirely based on ambient synchrophasor measurements. The proposed framework consists of three components, namely, input-output transfer function estimation, channel selection, and feedback control implementation. For the first part, we propose a simple yet effective novel estimation algorithm in the frequency domain to identify low-order transfer functions in pre-specified frequency ranges between the measured input and output data using ambient synchrophasor measurements. In the second part, based on the identified transfer functions, the joint controllability-observability (JCO) of all identified channels is estimated and most suitable control candidates for damping the target inter-area mode are selected. Finally, an appropriate lead-lag controller is designed using a classical frequency-domain method to improve the damping of a dominant oscillatory inter-area mode. Since ambient data is used in the analysis, the selected channel as well as the designed controller parameters can be updated online whenever the system operating point changes resulting in an efficient adaptive controller. The effectiveness of the proposed framework is illustrated by implementing it on the two-area Kundur test system and the IEEE 39-bus test system.
Keyword:
Adaptive feedback control
inter-area oscillations
joint controllability-observability
least-squares
oscillation damping control
phasor measurement unit (PMU)
transfer function identification
wide-area measurement system (WAMS)

期刊

IEEE Transactions on Power Systems 封面图
IEEE Transactions on Power Systems
IF:
7.2
论文数:
1.1W
被引数:
5.0W

机构

W
washington state university
学者数:
1.8W
论文数: 1.6W
被引数: 114
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