Robust dynamic and algebraic state estimation for microgrids: A generalized approach

Abstract Network control, optimization, and security analysis are facilitated by accurate microgrid state estimation. By utilizing phasor measurement units (PMUs), a combined robust centralized dynamic algebraic approach is proposed in this paper for estimating algebraic states (voltage phasors) as...

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Main Authors: Iraj Pourkeivani, Mehrdad Abedi, Shahram Montaser Kouhsari, Kazem Yaqoubi, Ali Fahimi
Format: Article
Language:English
Published: Wiley 2023-10-01
Series:IET Renewable Power Generation
Subjects:
Online Access:https://doi.org/10.1049/rpg2.12851
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author Iraj Pourkeivani
Mehrdad Abedi
Shahram Montaser Kouhsari
Kazem Yaqoubi
Ali Fahimi
author_facet Iraj Pourkeivani
Mehrdad Abedi
Shahram Montaser Kouhsari
Kazem Yaqoubi
Ali Fahimi
author_sort Iraj Pourkeivani
collection DOAJ
description Abstract Network control, optimization, and security analysis are facilitated by accurate microgrid state estimation. By utilizing phasor measurement units (PMUs), a combined robust centralized dynamic algebraic approach is proposed in this paper for estimating algebraic states (voltage phasors) as well as dynamic states (associated with synchronous generators and wind turbines). Assuming that a load is placed on each bus, an innovative PMU placement method is also presented to provide measurements for all dynamic and algebraic state variables. As a robust link between algebraic state estimation and dynamic state estimation, the output results of the least absolute value (LAV) estimator, which is robust against bad data, are fed to dynamic state estimators as pseudo measurements. Next, to address the nonlinearity of synchronous generator and wind turbine models, an unscented Kalman filter (UKF) is applied to estimate dynamic states precisely. The numerical tests on a microgrid test system show that the suggested approach is suitable for both algebraic and dynamic state estimation. Synchronous generators and wind turbines are modeled using nonlinear models of the 9th and third orders, respectively, and static loads are modeled as voltage‐frequency dependent ones.
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institution OA Journals
issn 1752-1416
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language English
publishDate 2023-10-01
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series IET Renewable Power Generation
spelling doaj-art-87f22b8013644a098f178bb844bb07262025-08-20T02:11:11ZengWileyIET Renewable Power Generation1752-14161752-14242023-10-0117133373338510.1049/rpg2.12851Robust dynamic and algebraic state estimation for microgrids: A generalized approachIraj Pourkeivani0Mehrdad Abedi1Shahram Montaser Kouhsari2Kazem Yaqoubi3Ali Fahimi4Department of Electrical Engineering Amirkabir University of Technology Tehran IranDepartment of Electrical Engineering Amirkabir University of Technology Tehran IranDepartment of Electrical Engineering Amirkabir University of Technology Tehran IranDepartment of Electrical Engineering Amirkabir University of Technology Tehran IranDepartment of Electrical Engineering Amirkabir University of Technology Tehran IranAbstract Network control, optimization, and security analysis are facilitated by accurate microgrid state estimation. By utilizing phasor measurement units (PMUs), a combined robust centralized dynamic algebraic approach is proposed in this paper for estimating algebraic states (voltage phasors) as well as dynamic states (associated with synchronous generators and wind turbines). Assuming that a load is placed on each bus, an innovative PMU placement method is also presented to provide measurements for all dynamic and algebraic state variables. As a robust link between algebraic state estimation and dynamic state estimation, the output results of the least absolute value (LAV) estimator, which is robust against bad data, are fed to dynamic state estimators as pseudo measurements. Next, to address the nonlinearity of synchronous generator and wind turbine models, an unscented Kalman filter (UKF) is applied to estimate dynamic states precisely. The numerical tests on a microgrid test system show that the suggested approach is suitable for both algebraic and dynamic state estimation. Synchronous generators and wind turbines are modeled using nonlinear models of the 9th and third orders, respectively, and static loads are modeled as voltage‐frequency dependent ones.https://doi.org/10.1049/rpg2.12851electric generatorsestimation theorypower system state estimationphasor measurementwind turbines
spellingShingle Iraj Pourkeivani
Mehrdad Abedi
Shahram Montaser Kouhsari
Kazem Yaqoubi
Ali Fahimi
Robust dynamic and algebraic state estimation for microgrids: A generalized approach
IET Renewable Power Generation
electric generators
estimation theory
power system state estimation
phasor measurement
wind turbines
title Robust dynamic and algebraic state estimation for microgrids: A generalized approach
title_full Robust dynamic and algebraic state estimation for microgrids: A generalized approach
title_fullStr Robust dynamic and algebraic state estimation for microgrids: A generalized approach
title_full_unstemmed Robust dynamic and algebraic state estimation for microgrids: A generalized approach
title_short Robust dynamic and algebraic state estimation for microgrids: A generalized approach
title_sort robust dynamic and algebraic state estimation for microgrids a generalized approach
topic electric generators
estimation theory
power system state estimation
phasor measurement
wind turbines
url https://doi.org/10.1049/rpg2.12851
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AT shahrammontaserkouhsari robustdynamicandalgebraicstateestimationformicrogridsageneralizedapproach
AT kazemyaqoubi robustdynamicandalgebraicstateestimationformicrogridsageneralizedapproach
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