Dynamic event-based forecasting-aided state estimation for active distribution systems subject to limited communication resource
In this paper, the dynamic event-based forecasting-aided state estimation (FASE) method is developed to deal with the state estimation problem of the active distribution system (ADS) subject to communication constraints and non-linear measurements. The proposed method first constructs a state-space...
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| Published in | Electric power systems research Vol. 221; p. 109417 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
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Elsevier B.V
01.08.2023
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| Abstract | In this paper, the dynamic event-based forecasting-aided state estimation (FASE) method is developed to deal with the state estimation problem of the active distribution system (ADS) subject to communication constraints and non-linear measurements. The proposed method first constructs a state-space model of the ADS to describe system state time evolution. Secondly, to use communication resources more effectively, the dynamic event-triggered scheme (ETS) is exploited to schedule the data transmission. Aiming at the problem of the ADS in the presence of the non-linear measurement, the Gaussian integral is approximated by the spherical cubature rule to obtain the mean and covariance of the state variables after non-linear transformation. Moreover, the upper bound of the estimation error covariance containing non-triggering errors is derived, and then minimized by suitably designing filter gain, thus developing the dynamic event-triggered cubature Kalman filter (DET-CKF) algorithm to perform state estimation for ADSs. Finally, a series of simulation experiments are conducted to verify the effectiveness of the developed FASE method.
•Dynamic event-triggered scheme can relieve the network transmission burden.•The upper bound of error covariance containing non-triggering errors is derived.•The spherical cubature rule is adopted to deal with non-linear measurement. |
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| AbstractList | In this paper, the dynamic event-based forecasting-aided state estimation (FASE) method is developed to deal with the state estimation problem of the active distribution system (ADS) subject to communication constraints and non-linear measurements. The proposed method first constructs a state-space model of the ADS to describe system state time evolution. Secondly, to use communication resources more effectively, the dynamic event-triggered scheme (ETS) is exploited to schedule the data transmission. Aiming at the problem of the ADS in the presence of the non-linear measurement, the Gaussian integral is approximated by the spherical cubature rule to obtain the mean and covariance of the state variables after non-linear transformation. Moreover, the upper bound of the estimation error covariance containing non-triggering errors is derived, and then minimized by suitably designing filter gain, thus developing the dynamic event-triggered cubature Kalman filter (DET-CKF) algorithm to perform state estimation for ADSs. Finally, a series of simulation experiments are conducted to verify the effectiveness of the developed FASE method.
•Dynamic event-triggered scheme can relieve the network transmission burden.•The upper bound of error covariance containing non-triggering errors is derived.•The spherical cubature rule is adopted to deal with non-linear measurement. |
| ArticleNumber | 109417 |
| Author | Zheng, Xinlei Zhang, Jiaan Powell, Kody Bai, Xingzhen Liao, Wenlong Ge, Leijiao |
| Author_xml | – sequence: 1 givenname: Xingzhen surname: Bai fullname: Bai, Xingzhen email: xzbai@163.com organization: College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266590, China – sequence: 2 givenname: Xinlei orcidid: 0000-0003-3271-6903 surname: Zheng fullname: Zheng, Xinlei email: zhengxl97@163.com organization: School of Electrical Engineering, Southeast University, Nanjing 210096, China – sequence: 3 givenname: Leijiao orcidid: 0000-0001-6310-6986 surname: Ge fullname: Ge, Leijiao email: legendglj99@tju.edu.cn organization: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China – sequence: 4 givenname: Wenlong surname: Liao fullname: Liao, Wenlong email: weli@energy.aau.dk organization: AAU Energy, Aalborg University, Aalborg 9220, Denmark – sequence: 5 givenname: Kody orcidid: 0000-0001-9904-6671 surname: Powell fullname: Powell, Kody email: kody.powell@utah.edu organization: Department of Chemical Engineering, University of Utah, UT 84112, United States of America – sequence: 6 givenname: Jiaan orcidid: 0000-0003-3836-3491 surname: Zhang fullname: Zhang, Jiaan email: zhangjiaan@foxmail.com organization: School of Electrical and Engineering, Hebei University of Technology, Tianjin 300401, China |
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| Keywords | Cubature Kalman filter Dynamic event-triggered scheme Active distribution system Non-linear system State estimation |
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| SubjectTerms | Active distribution system Cubature Kalman filter Dynamic event-triggered scheme Non-linear system State estimation |
| Title | Dynamic event-based forecasting-aided state estimation for active distribution systems subject to limited communication resource |
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