EKF-based Predictive Stabilization of Shipboard DC Microgrids with Uncertain Time-varying Load

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Abstract

The performance of dc shipboard power systems (SPSs) may degrade due to the negative impedance of constant power loads (CPLs) connected to dc microgrids (MGs). To control the dcSPS effectively, estimation of the instantaneous power flow to the time-varying uncertain CPLs is necessary. Furthermore, fast adaptive control is needed to deal with changes in the CPL power flow and quick stabilization of the dc MGs. Such a controller typically uses injection current from an energy storage system for actuation. Since measuring the CPLs' powers require installing current sensors that are both costly and not optimal, an estimation of the CPLs' powers should be employed. In this paper, an extended Kalman filter (EKF) is developed to estimate a time-varying power of uncertain CPLs in a dc MG based on measuring capacitor voltages. The estimated power is then used in a Takagi-Sugeno fuzzy-based model predictive controller (MPC) to manipulate the energy storage unit. The proposed approach is tested experimentally on a dc MG that feeds a single CPL. The experimental results show that the proposed MPC controller alongside the developed EKF improves the transient performance and the stability margin of the dc MGs used in the SPSs.

Original languageEnglish
Article number8590740
JournalI E E E Journal of Emerging and Selected Topics in Power Electronics
Volume7
Issue number2
Pages (from-to)901-909
Number of pages9
ISSN2168-6777
DOIs
Publication statusPublished - 1 Jun 2019

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Extended Kalman filters
Stabilization
Controllers
Energy storage
Capacitors
Sensors
Electric potential

Keywords

  • Constant power load (CPL)
  • DC microgrid (MG)
  • Takagi-Sugeno (TS) fuzzy model
  • extended Kalman filter (EKF)
  • model predictive control (MPC)
  • shipboard power system (SPS)

Cite this

@article{b26ff470fa8b4f86999f33587b1a07b0,
title = "EKF-based Predictive Stabilization of Shipboard DC Microgrids with Uncertain Time-varying Load",
abstract = "The performance of dc shipboard power systems (SPSs) may degrade due to the negative impedance of constant power loads (CPLs) connected to dc microgrids (MGs). To control the dcSPS effectively, estimation of the instantaneous power flow to the time-varying uncertain CPLs is necessary. Furthermore, fast adaptive control is needed to deal with changes in the CPL power flow and quick stabilization of the dc MGs. Such a controller typically uses injection current from an energy storage system for actuation. Since measuring the CPLs' powers require installing current sensors that are both costly and not optimal, an estimation of the CPLs' powers should be employed. In this paper, an extended Kalman filter (EKF) is developed to estimate a time-varying power of uncertain CPLs in a dc MG based on measuring capacitor voltages. The estimated power is then used in a Takagi-Sugeno fuzzy-based model predictive controller (MPC) to manipulate the energy storage unit. The proposed approach is tested experimentally on a dc MG that feeds a single CPL. The experimental results show that the proposed MPC controller alongside the developed EKF improves the transient performance and the stability margin of the dc MGs used in the SPSs.",
keywords = "Constant power load (CPL), DC microgrid (MG), Takagi-Sugeno (TS) fuzzy model, extended Kalman filter (EKF), model predictive control (MPC), shipboard power system (SPS)",
author = "Shirin Yousefizadeh and Bendtsen, {Jan Dimon} and Navid Vafamand and Khooban, {Mohammad Hassan} and Tomislav Dragicevic and Frede Bl{\aa}bjerg",
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EKF-based Predictive Stabilization of Shipboard DC Microgrids with Uncertain Time-varying Load. / Yousefizadeh, Shirin; Bendtsen, Jan Dimon; Vafamand, Navid; Khooban, Mohammad Hassan; Dragicevic, Tomislav; Blåbjerg, Frede.

In: I E E E Journal of Emerging and Selected Topics in Power Electronics, Vol. 7, No. 2, 8590740, 01.06.2019, p. 901-909.

Research output: Contribution to journalJournal articleResearchpeer-review

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T1 - EKF-based Predictive Stabilization of Shipboard DC Microgrids with Uncertain Time-varying Load

AU - Yousefizadeh, Shirin

AU - Bendtsen, Jan Dimon

AU - Vafamand, Navid

AU - Khooban, Mohammad Hassan

AU - Dragicevic, Tomislav

AU - Blåbjerg, Frede

PY - 2019/6/1

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N2 - The performance of dc shipboard power systems (SPSs) may degrade due to the negative impedance of constant power loads (CPLs) connected to dc microgrids (MGs). To control the dcSPS effectively, estimation of the instantaneous power flow to the time-varying uncertain CPLs is necessary. Furthermore, fast adaptive control is needed to deal with changes in the CPL power flow and quick stabilization of the dc MGs. Such a controller typically uses injection current from an energy storage system for actuation. Since measuring the CPLs' powers require installing current sensors that are both costly and not optimal, an estimation of the CPLs' powers should be employed. In this paper, an extended Kalman filter (EKF) is developed to estimate a time-varying power of uncertain CPLs in a dc MG based on measuring capacitor voltages. The estimated power is then used in a Takagi-Sugeno fuzzy-based model predictive controller (MPC) to manipulate the energy storage unit. The proposed approach is tested experimentally on a dc MG that feeds a single CPL. The experimental results show that the proposed MPC controller alongside the developed EKF improves the transient performance and the stability margin of the dc MGs used in the SPSs.

AB - The performance of dc shipboard power systems (SPSs) may degrade due to the negative impedance of constant power loads (CPLs) connected to dc microgrids (MGs). To control the dcSPS effectively, estimation of the instantaneous power flow to the time-varying uncertain CPLs is necessary. Furthermore, fast adaptive control is needed to deal with changes in the CPL power flow and quick stabilization of the dc MGs. Such a controller typically uses injection current from an energy storage system for actuation. Since measuring the CPLs' powers require installing current sensors that are both costly and not optimal, an estimation of the CPLs' powers should be employed. In this paper, an extended Kalman filter (EKF) is developed to estimate a time-varying power of uncertain CPLs in a dc MG based on measuring capacitor voltages. The estimated power is then used in a Takagi-Sugeno fuzzy-based model predictive controller (MPC) to manipulate the energy storage unit. The proposed approach is tested experimentally on a dc MG that feeds a single CPL. The experimental results show that the proposed MPC controller alongside the developed EKF improves the transient performance and the stability margin of the dc MGs used in the SPSs.

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KW - model predictive control (MPC)

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DO - 10.1109/JESTPE.2018.2889971

M3 - Journal article

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EP - 909

JO - I E E E Journal of Emerging and Selected Topics in Power Electronics

JF - I E E E Journal of Emerging and Selected Topics in Power Electronics

SN - 2168-6777

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