Event-trigger extended Kalman filter design for distributed generation network with limited communication

Xing Xin; Luyu Li; Sen Li; Zhen Li; Jian Li; Zhen Chen; Xiangdong Liu

doi:10.23919/ChiCC.2017.8027599

Event-trigger extended Kalman filter design for distributed generation network with limited communication

Xing Xin
, Luyu Li
, Sen Li
, Zhen Li^*
, Jian Li
, Zhen Chen
, Xiangdong Liu

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

For distributed generation (DG) network, it is important to estimate the real-time states. The information-centric networking (ICN) is established to take charge of the communication of DG network. However, the assumption of ideal communication between sensors and the estimation center cannot be guaranteed due to the communication constraints of ICN with the increasing DG network. A conventional algorithm, which reduces the communication burden in ICN, is to drop the observation of each smart grid in a random way. However, the accuracy of this algorithm recession decays rapidly with the increasing drop rate. To guarantee an appropriate estimation accuracy when the drop rate increases, this paper introduces the event-trigger strategy into the estimation algorithm. An event-trigger extended Kalman filter (ET-EKF) is established in this paper to adapt the nonlinearity of DG system. ET-EKF reduces the communication burden and achieves an appropriate estimation accuracy at the same time. Finally, its feasibility and performance are demonstrated using the standard IEEE 39-bus system with phasor measurement units (PMUs).

Original language	English
Title of host publication	Proceedings of the 36th Chinese Control Conference, CCC 2017
Editors	Tao Liu, Qianchuan Zhao
Publisher	IEEE Computer Society
Pages	1717-1722
Number of pages	6
ISBN (Electronic)	9789881563934
DOIs	https://doi.org/10.23919/ChiCC.2017.8027599
Publication status	Published - 7 Sept 2017
Event	36th Chinese Control Conference, CCC 2017 - Dalian, China Duration: 26 Jul 2017 → 28 Jul 2017

Publication series

Name	Chinese Control Conference, CCC
ISSN (Print)	1934-1768
ISSN (Electronic)	2161-2927

Conference

Conference	36th Chinese Control Conference, CCC 2017
Country/Territory	China
City	Dalian
Period	26/07/17 → 28/07/17

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Event-trigger extended Kalman filter (ET-EKF)
distributed generation network
phasor measurement unit (PMU)
real-time estimation
smart grids

Access to Document

10.23919/ChiCC.2017.8027599

Cite this

Xin, X., Li, L., Li, S., Li, Z., Li, J., Chen, Z., & Liu, X. (2017). Event-trigger extended Kalman filter design for distributed generation network with limited communication. In T. Liu, & Q. Zhao (Eds.), Proceedings of the 36th Chinese Control Conference, CCC 2017 (pp. 1717-1722). Article 8027599 (Chinese Control Conference, CCC). IEEE Computer Society. https://doi.org/10.23919/ChiCC.2017.8027599

@inproceedings{54a7fa3927414c02b320b6722aa96c65,

title = "Event-trigger extended Kalman filter design for distributed generation network with limited communication",

abstract = "For distributed generation (DG) network, it is important to estimate the real-time states. The information-centric networking (ICN) is established to take charge of the communication of DG network. However, the assumption of ideal communication between sensors and the estimation center cannot be guaranteed due to the communication constraints of ICN with the increasing DG network. A conventional algorithm, which reduces the communication burden in ICN, is to drop the observation of each smart grid in a random way. However, the accuracy of this algorithm recession decays rapidly with the increasing drop rate. To guarantee an appropriate estimation accuracy when the drop rate increases, this paper introduces the event-trigger strategy into the estimation algorithm. An event-trigger extended Kalman filter (ET-EKF) is established in this paper to adapt the nonlinearity of DG system. ET-EKF reduces the communication burden and achieves an appropriate estimation accuracy at the same time. Finally, its feasibility and performance are demonstrated using the standard IEEE 39-bus system with phasor measurement units (PMUs).",

keywords = "Event-trigger extended Kalman filter (ET-EKF), distributed generation network, phasor measurement unit (PMU), real-time estimation, smart grids",

author = "Xing Xin and Luyu Li and Sen Li and Zhen Li and Jian Li and Zhen Chen and Xiangdong Liu",

note = "Publisher Copyright: {\textcopyright} 2017 Technical Committee on Control Theory, CAA.; 36th Chinese Control Conference, CCC 2017 ; Conference date: 26-07-2017 Through 28-07-2017",

year = "2017",

month = sep,

day = "7",

doi = "10.23919/ChiCC.2017.8027599",

language = "English",

series = "Chinese Control Conference, CCC",

publisher = "IEEE Computer Society",

pages = "1717--1722",

editor = "Tao Liu and Qianchuan Zhao",

booktitle = "Proceedings of the 36th Chinese Control Conference, CCC 2017",

address = "United States",

}

Xin, X, Li, L, Li, S, Li, Z , Li, J, Chen, Z & Liu, X 2017, Event-trigger extended Kalman filter design for distributed generation network with limited communication. in T Liu & Q Zhao (eds), Proceedings of the 36th Chinese Control Conference, CCC 2017., 8027599, Chinese Control Conference, CCC, IEEE Computer Society, pp. 1717-1722, 36th Chinese Control Conference, CCC 2017, Dalian, China, 26/07/17. https://doi.org/10.23919/ChiCC.2017.8027599

Event-trigger extended Kalman filter design for distributed generation network with limited communication. / Xin, Xing; Li, Luyu; Li, Sen et al.
Proceedings of the 36th Chinese Control Conference, CCC 2017. ed. / Tao Liu; Qianchuan Zhao. IEEE Computer Society, 2017. p. 1717-1722 8027599 (Chinese Control Conference, CCC).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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AU - Xin, Xing

AU - Li, Luyu

AU - Li, Sen

AU - Li, Zhen

AU - Li, Jian

AU - Chen, Zhen

AU - Liu, Xiangdong

PY - 2017/9/7

Y1 - 2017/9/7

N2 - For distributed generation (DG) network, it is important to estimate the real-time states. The information-centric networking (ICN) is established to take charge of the communication of DG network. However, the assumption of ideal communication between sensors and the estimation center cannot be guaranteed due to the communication constraints of ICN with the increasing DG network. A conventional algorithm, which reduces the communication burden in ICN, is to drop the observation of each smart grid in a random way. However, the accuracy of this algorithm recession decays rapidly with the increasing drop rate. To guarantee an appropriate estimation accuracy when the drop rate increases, this paper introduces the event-trigger strategy into the estimation algorithm. An event-trigger extended Kalman filter (ET-EKF) is established in this paper to adapt the nonlinearity of DG system. ET-EKF reduces the communication burden and achieves an appropriate estimation accuracy at the same time. Finally, its feasibility and performance are demonstrated using the standard IEEE 39-bus system with phasor measurement units (PMUs).

AB - For distributed generation (DG) network, it is important to estimate the real-time states. The information-centric networking (ICN) is established to take charge of the communication of DG network. However, the assumption of ideal communication between sensors and the estimation center cannot be guaranteed due to the communication constraints of ICN with the increasing DG network. A conventional algorithm, which reduces the communication burden in ICN, is to drop the observation of each smart grid in a random way. However, the accuracy of this algorithm recession decays rapidly with the increasing drop rate. To guarantee an appropriate estimation accuracy when the drop rate increases, this paper introduces the event-trigger strategy into the estimation algorithm. An event-trigger extended Kalman filter (ET-EKF) is established in this paper to adapt the nonlinearity of DG system. ET-EKF reduces the communication burden and achieves an appropriate estimation accuracy at the same time. Finally, its feasibility and performance are demonstrated using the standard IEEE 39-bus system with phasor measurement units (PMUs).

KW - Event-trigger extended Kalman filter (ET-EKF)

KW - distributed generation network

KW - phasor measurement unit (PMU)

KW - real-time estimation

KW - smart grids

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U2 - 10.23919/ChiCC.2017.8027599

DO - 10.23919/ChiCC.2017.8027599

M3 - Conference contribution

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EP - 1722

BT - Proceedings of the 36th Chinese Control Conference, CCC 2017

A2 - Liu, Tao

A2 - Zhao, Qianchuan

PB - IEEE Computer Society

T2 - 36th Chinese Control Conference, CCC 2017

Y2 - 26 July 2017 through 28 July 2017

ER -

Event-trigger extended Kalman filter design for distributed generation network with limited communication

Abstract

Publication series

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UN SDGs

Keywords

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