Variance analysis of robust state estimation in power system using influence function
An analytical equation is derived using influence function approximation to calculate the variance of the state estimate for traditional robust state estimators such as the Quadratic-Constant, Quadratic-Linear, Square-Root, Schweppe-Huber Generalized-M and Multiple-Segment estimator. The equation gi...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2017
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/83621 http://hdl.handle.net/10220/42695 |
| _version_ | 1826120132360929280 |
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| author | Ho, Weng Khuen Chen, Tengpeng Ling, Keck Voon Sun, Lu |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Ho, Weng Khuen Chen, Tengpeng Ling, Keck Voon Sun, Lu |
| author_sort | Ho, Weng Khuen |
| collection | NTU |
| description | An analytical equation is derived using influence function approximation to calculate the variance of the state estimate for traditional robust state estimators such as the Quadratic-Constant, Quadratic-Linear, Square-Root, Schweppe-Huber Generalized-M and Multiple-Segment estimator. The equation gives insights into the precision of the estimation. Using the equation, the variance of a state estimate can be expressed as a function of measurement noise variances enabling the selection of sensors for a specified estimator precision. It can also be used to search for the optimum estimator parameters to give the minimum sum of variances. The well-known Weighted-Least-Squares variance formula is a special case of the equation and simulations on the IEEE 14-bus system are given to show the usefulness of the equation. |
| first_indexed | 2024-10-01T05:11:12Z |
| format | Journal Article |
| id | ntu-10356/83621 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:11:12Z |
| publishDate | 2017 |
| record_format | dspace |
| spelling | ntu-10356/836212020-03-07T13:57:27Z Variance analysis of robust state estimation in power system using influence function Ho, Weng Khuen Chen, Tengpeng Ling, Keck Voon Sun, Lu School of Electrical and Electronic Engineering Robust state estimation M-estimator An analytical equation is derived using influence function approximation to calculate the variance of the state estimate for traditional robust state estimators such as the Quadratic-Constant, Quadratic-Linear, Square-Root, Schweppe-Huber Generalized-M and Multiple-Segment estimator. The equation gives insights into the precision of the estimation. Using the equation, the variance of a state estimate can be expressed as a function of measurement noise variances enabling the selection of sensors for a specified estimator precision. It can also be used to search for the optimum estimator parameters to give the minimum sum of variances. The well-known Weighted-Least-Squares variance formula is a special case of the equation and simulations on the IEEE 14-bus system are given to show the usefulness of the equation. NRF (Natl Research Foundation, S’pore) Accepted version 2017-06-14T04:09:56Z 2019-12-06T15:26:55Z 2017-06-14T04:09:56Z 2019-12-06T15:26:55Z 2017 Journal Article Ho, W. K., Chen, T., Ling, K. V., & Sun, L. (2017). Variance analysis of robust state estimation in power system using influence function. International Journal of Electrical Power & Energy Systems, 92, 53-62. 0142-0615 https://hdl.handle.net/10356/83621 http://hdl.handle.net/10220/42695 10.1016/j.ijepes.2017.04.009 en International Journal of Electrical Power & Energy Systems © 2017 Elsevier. This is the author created version of a work that has been peer reviewed and accepted for publication by International Journal of Electrical Power & Energy Systems, Elsevier. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1016/j.ijepes.2017.04.009]. 20 p. application/pdf |
| spellingShingle | Robust state estimation M-estimator Ho, Weng Khuen Chen, Tengpeng Ling, Keck Voon Sun, Lu Variance analysis of robust state estimation in power system using influence function |
| title | Variance analysis of robust state estimation in power system using influence function |
| title_full | Variance analysis of robust state estimation in power system using influence function |
| title_fullStr | Variance analysis of robust state estimation in power system using influence function |
| title_full_unstemmed | Variance analysis of robust state estimation in power system using influence function |
| title_short | Variance analysis of robust state estimation in power system using influence function |
| title_sort | variance analysis of robust state estimation in power system using influence function |
| topic | Robust state estimation M-estimator |
| url | https://hdl.handle.net/10356/83621 http://hdl.handle.net/10220/42695 |
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