Robust and Fast State Estimation for Poorly-Observable Low Voltage Distribution Networks Based on the Kalman Filter Algorithm
This paper presents a novel approach for the state estimation of poorly-observable low voltage distribution networks, characterized by intermittent and erroneous measurements. The developed state estimation algorithm is based on the Extended Kalman filter, where we have modified the execution of the...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-11-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/12/23/4457 |
| _version_ | 1811303181181779968 |
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| author | Mitja Antončič Igor Papič Boštjan Blažič |
| author_facet | Mitja Antončič Igor Papič Boštjan Blažič |
| author_sort | Mitja Antončič |
| collection | DOAJ |
| description | This paper presents a novel approach for the state estimation of poorly-observable low voltage distribution networks, characterized by intermittent and erroneous measurements. The developed state estimation algorithm is based on the Extended Kalman filter, where we have modified the execution of the filtering process. Namely, we have fixed the Kalman gain and Jacobian matrices to constant matrices; their values change only after a larger disturbance in the network. This allows for a fast and robust estimation of the network state. The performance of the proposed state-estimation algorithm is validated by means of simulations of an actual low-voltage network with actual field measurement data. Two different cases are presented. The results of the developed state estimator are compared to a classical estimator based on the weighted least squares method. The comparison shows that the developed state estimator outperforms the classical one in terms of calculation speed and, in case of spurious measurements errors, also in terms of accuracy. |
| first_indexed | 2024-04-13T07:43:27Z |
| format | Article |
| id | doaj.art-3692ed86a79b45179dd5bb6601b000ed |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-13T07:43:27Z |
| publishDate | 2019-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-3692ed86a79b45179dd5bb6601b000ed2022-12-22T02:55:48ZengMDPI AGEnergies1996-10732019-11-011223445710.3390/en12234457en12234457Robust and Fast State Estimation for Poorly-Observable Low Voltage Distribution Networks Based on the Kalman Filter AlgorithmMitja Antončič0Igor Papič1Boštjan Blažič2Faculty of Electrical Engineering, University of Ljubljana, Tržaška 25, 1000 Ljubljana, SloveniaFaculty of Electrical Engineering, University of Ljubljana, Tržaška 25, 1000 Ljubljana, SloveniaFaculty of Electrical Engineering, University of Ljubljana, Tržaška 25, 1000 Ljubljana, SloveniaThis paper presents a novel approach for the state estimation of poorly-observable low voltage distribution networks, characterized by intermittent and erroneous measurements. The developed state estimation algorithm is based on the Extended Kalman filter, where we have modified the execution of the filtering process. Namely, we have fixed the Kalman gain and Jacobian matrices to constant matrices; their values change only after a larger disturbance in the network. This allows for a fast and robust estimation of the network state. The performance of the proposed state-estimation algorithm is validated by means of simulations of an actual low-voltage network with actual field measurement data. Two different cases are presented. The results of the developed state estimator are compared to a classical estimator based on the weighted least squares method. The comparison shows that the developed state estimator outperforms the classical one in terms of calculation speed and, in case of spurious measurements errors, also in terms of accuracy.https://www.mdpi.com/1996-1073/12/23/4457state estimationlow voltagepoor observabilitykalmanforecast-aided state estimatorweighted least squareslow-voltage state estimation |
| spellingShingle | Mitja Antončič Igor Papič Boštjan Blažič Robust and Fast State Estimation for Poorly-Observable Low Voltage Distribution Networks Based on the Kalman Filter Algorithm Energies state estimation low voltage poor observability kalman forecast-aided state estimator weighted least squares low-voltage state estimation |
| title | Robust and Fast State Estimation for Poorly-Observable Low Voltage Distribution Networks Based on the Kalman Filter Algorithm |
| title_full | Robust and Fast State Estimation for Poorly-Observable Low Voltage Distribution Networks Based on the Kalman Filter Algorithm |
| title_fullStr | Robust and Fast State Estimation for Poorly-Observable Low Voltage Distribution Networks Based on the Kalman Filter Algorithm |
| title_full_unstemmed | Robust and Fast State Estimation for Poorly-Observable Low Voltage Distribution Networks Based on the Kalman Filter Algorithm |
| title_short | Robust and Fast State Estimation for Poorly-Observable Low Voltage Distribution Networks Based on the Kalman Filter Algorithm |
| title_sort | robust and fast state estimation for poorly observable low voltage distribution networks based on the kalman filter algorithm |
| topic | state estimation low voltage poor observability kalman forecast-aided state estimator weighted least squares low-voltage state estimation |
| url | https://www.mdpi.com/1996-1073/12/23/4457 |
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