Robust Frequency Divider for Power System Online Monitoring and Control

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Title: Robust Frequency Divider for Power System Online Monitoring and Control
Authors: Zhao, Junbo
Mili, Lamine
Milano, Federico
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Date: Jul-2018
Online since: 2019-04-17T10:36:31Z
Abstract: Accurate local bus frequency is essential for power system frequency regulation provided by distributed energy sources, flexible loads, and among others. This paper proposes a robust frequency divider (RFD) for online bus frequency estimation. Our RFD is independent of the load models, and the knowledge of swing equation parameters, transmission line parameters, and local Phasor Measurement Unit (PMU) measurements at each generator terminal bus is sufficient. In addition, it is able to handle several types of data quality issues, such as measurement noise, gross measurement errors, cyberattacks, and measurement losses. Furthermore, the proposed RFD contains the decentralized estimation of local generator rotor speeds and the centralized bus frequency estimation, which resembles the structure of the decentralized/hierarchical control scheme. This enables RFD for very large-scale system applications. Specifically, we decouple each generator from the rest of the system by treating metered real power injection as inputs and the frequency measurements provided by PMU as outputs; then a robust unscented Kalman filter based dynamic state estimator is proposed for local generator rotor speed estimation; finally, these rotor speeds are transmitted to control center for bus frequency estimation. Numerical results carried out on the IEEE 39-bus and 145-bus systems demonstrate the effectiveness and robustness of the proposed method.
Funding Details: European Commission Horizon 2020
Science Foundation Ireland
Type of material: Journal Article
Publisher: IEE
Journal: IEEE Transactions on Power Systems
Volume: 33
Issue: 4
Start page: 4414
End page: 4423
Copyright (published version): 2018 IEEE
Keywords: Frequency estimationFrequency controlRobust statisticsDecentralized estimationDynamic state estimationUnscented Kalman filterPower systems dynamicsStability
DOI: 10.1109/TPWRS.2017.2785348
Language: en
Status of Item: Peer reviewed
Appears in Collections:Electrical and Electronic Engineering Research Collection

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