Bad data correction in harmonic state estimation for power distribution systems: an approach based on generalised pattern search algorithm
•A novel methodology is proposed for bad data correction in harmonic state estimation;•Bad data is detected, identified and corrected assuming a limited number of measurements;•Three-phase distribution systems are considered for the computational simulations;•Generalized pattern search algorithm is...
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| Vydané v: | Electric power systems research Ročník 204; s. 107684 |
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| Médium: | Journal Article |
| Jazyk: | English |
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Amsterdam
Elsevier B.V
01.03.2022
Elsevier Science Ltd |
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| ISSN: | 0378-7796, 1873-2046 |
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| Abstract | •A novel methodology is proposed for bad data correction in harmonic state estimation;•Bad data is detected, identified and corrected assuming a limited number of measurements;•Three-phase distribution systems are considered for the computational simulations;•Generalized pattern search algorithm is used to determine correction factors for bad data.
This paper presents a novel methodology for bad data correction in harmonic state estimation for power distribution systems. An optimisation model is formulated considering an objective function to be minimised based on the weighted least squares. Inequality constraints are incorporated to the problem for those buses which are not monitored in real time by any dedicated meter, being their corresponding active and reactive powers considered between upper and lower bounds in order to provide supplementary information about the current system state. In this paper, a measurement calibration vector is introduced into the optimisation model, assuming that a correction factor is associated with the measurements gathered from the network. GPSA (Generalized Pattern Search Algorithm) is used to determine the optimal values of each calibration factor to provide correct state estimation results. A 69-bus test system is used for the computational simulations considering different case studies with multiple bad data to be identified and corrected proving the efficiency and viability of the proposed method. The main contribution of this work is the automatic detection of bad data, identification of the corrupted measurements and correction of the bad data ensuring that the system states are estimated with errors lower than 1%. |
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| AbstractList | This paper presents a novel methodology for bad data correction in harmonic state estimation for power distribution systems. An optimisation model is formulated considering an objective function to be minimised based on the weighted least squares. Inequality constraints are incorporated to the problem for those buses which are not monitored in real time by any dedicated meter, being their corresponding active and reactive powers considered between upper and lower bounds in order to provide supplementary information about the current system state. In this paper, a measurement calibration vector is introduced into the optimisation model, assuming that a correction factor is associated with the measurements gathered from the network. GPSA (Generalized Pattern Search Algorithm) is used to determine the optimal values of each calibration factor to provide correct state estimation results. A 69-bus test system is used for the computational simulations considering different case studies with multiple bad data to be identified and corrected proving the efficiency and viability of the proposed method. The main contribution of this work is the automatic detection of bad data, identification of the corrupted measurements and correction of the bad data ensuring that the system states are estimated with errors lower than 1%. •A novel methodology is proposed for bad data correction in harmonic state estimation;•Bad data is detected, identified and corrected assuming a limited number of measurements;•Three-phase distribution systems are considered for the computational simulations;•Generalized pattern search algorithm is used to determine correction factors for bad data. This paper presents a novel methodology for bad data correction in harmonic state estimation for power distribution systems. An optimisation model is formulated considering an objective function to be minimised based on the weighted least squares. Inequality constraints are incorporated to the problem for those buses which are not monitored in real time by any dedicated meter, being their corresponding active and reactive powers considered between upper and lower bounds in order to provide supplementary information about the current system state. In this paper, a measurement calibration vector is introduced into the optimisation model, assuming that a correction factor is associated with the measurements gathered from the network. GPSA (Generalized Pattern Search Algorithm) is used to determine the optimal values of each calibration factor to provide correct state estimation results. A 69-bus test system is used for the computational simulations considering different case studies with multiple bad data to be identified and corrected proving the efficiency and viability of the proposed method. The main contribution of this work is the automatic detection of bad data, identification of the corrupted measurements and correction of the bad data ensuring that the system states are estimated with errors lower than 1%. |
| ArticleNumber | 107684 |
| Author | Antunes, Matheus P. Melo, Igor D. |
| Author_xml | – sequence: 1 givenname: Igor D. surname: Melo fullname: Melo, Igor D. email: igor.delgado2008@engenharia.ufjf.br – sequence: 2 givenname: Matheus P. surname: Antunes fullname: Antunes, Matheus P. |
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| Cites_doi | 10.1016/j.epsr.2017.03.031 10.1109/61.311191 10.1049/iet-gtd.2020.0487 10.3390/e22030323 10.1109/TIM.2009.2019319 10.35833/MPCE.2019.000457 10.1109/TPAS.1983.318053 10.1109/TSG.2019.2938733 10.1109/TPAS.1971.292925 10.1109/TSG.2016.2590599 10.1016/j.epsr.2017.05.021 10.1016/j.epsr.2010.01.009 10.1049/iet-gtd.2016.1278 10.1016/j.epsr.2019.01.033 10.3390/electronics8020135 10.3390/e22010065 10.1109/TII.2018.2790931 10.1109/TPWRD.2004.833895 10.1016/j.ijepes.2020.106243 10.1016/j.epsr.2019.106063 10.1109/T-PAS.1975.31858 10.1109/61.19248 10.1016/j.epsr.2017.07.029 10.1016/j.epsr.2017.02.027 10.1016/j.epsr.2020.106276 |
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| Keywords | Distribution systems Power quality Bad data State estimation Harmonic state estimation |
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| Snippet | •A novel methodology is proposed for bad data correction in harmonic state estimation;•Bad data is detected, identified and corrected assuming a limited number... This paper presents a novel methodology for bad data correction in harmonic state estimation for power distribution systems. An optimisation model is... |
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| SubjectTerms | Bad data Calibration Distribution systems Electric power distribution Electricity distribution Estimating techniques Harmonic analysis Harmonic state estimation Lower bounds Mathematical models Optimization Pattern search Power quality Search algorithms State estimation |
| Title | Bad data correction in harmonic state estimation for power distribution systems: an approach based on generalised pattern search algorithm |
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