Phasor estimation in power systems using a neural network with online training for numerical relays purposes
There are a few components of the current signal that may lead to inaccurate current measurement in power systems, and therefore, may cause malfunction on numerical protective relays and control devices. Some of these components include harmonics, the decaying DC offset, and noises. In this study, a...
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| Published in | IET science, measurement & technology Vol. 9; no. 7; pp. 836 - 841 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
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The Institution of Engineering and Technology
01.10.2015
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| Abstract | There are a few components of the current signal that may lead to inaccurate current measurement in power systems, and therefore, may cause malfunction on numerical protective relays and control devices. Some of these components include harmonics, the decaying DC offset, and noises. In this study, a phasor estimation method based on artificial neural networks is proposed, which will provide fast response time and accuracy. The method uses the multilayer perceptron structure to precisely estimate the amplitude and phase angle of the current waveform by determining its input weights during an online training process. The proposed algorithm is tested and compared with other reliable and well-known methods for a performance evaluation. |
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| AbstractList | There are a few components of the current signal that may lead to inaccurate current measurement in power systems, and therefore, may cause malfunction on numerical protective relays and control devices. Some of these components include harmonics, the decaying DC offset, and noises. In this study, a phasor estimation method based on artificial neural networks is proposed, which will provide fast response time and accuracy. The method uses the multilayer perceptron structure to precisely estimate the amplitude and phase angle of the current waveform by determining its input weights during an online training process. The proposed algorithm is tested and compared with other reliable and well-known methods for a performance evaluation. |
| Author | Marchesan, Gustavo da Silva, Chrystian Dalla Lana Cardoso Junior, Ghendy Mariotto, Lenois |
| Author_xml | – sequence: 1 givenname: Chrystian Dalla Lana surname: da Silva fullname: da Silva, Chrystian Dalla Lana email: chrystiands@gmail.com organization: Federal University of Santa Maria, Avenida Roraima, 1000, Camobi 97105-900, Santa Maria, Rio Grande do Sul, Brazil – sequence: 2 givenname: Ghendy surname: Cardoso Junior fullname: Cardoso Junior, Ghendy organization: Federal University of Santa Maria, Avenida Roraima, 1000, Camobi 97105-900, Santa Maria, Rio Grande do Sul, Brazil – sequence: 3 givenname: Lenois surname: Mariotto fullname: Mariotto, Lenois organization: Federal University of Santa Maria, Avenida Roraima, 1000, Camobi 97105-900, Santa Maria, Rio Grande do Sul, Brazil – sequence: 4 givenname: Gustavo surname: Marchesan fullname: Marchesan, Gustavo organization: Federal University of Santa Maria, Avenida Roraima, 1000, Camobi 97105-900, Santa Maria, Rio Grande do Sul, Brazil |
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| CitedBy_id | crossref_primary_10_1007_s13198_021_01082_2 crossref_primary_10_1049_iet_smt_2017_0028 crossref_primary_10_1109_TPWRD_2019_2929246 crossref_primary_10_1016_j_epsr_2017_02_023 crossref_primary_10_1049_iet_gtd_2017_0446 crossref_primary_10_3390_en14217112 crossref_primary_10_1016_j_epsr_2020_106316 crossref_primary_10_1016_j_epsr_2023_109280 crossref_primary_10_1016_j_epsr_2016_08_034 crossref_primary_10_1049_iet_smt_2018_5390 crossref_primary_10_1109_TPWRD_2016_2629762 crossref_primary_10_1016_j_epsr_2019_106124 crossref_primary_10_1016_j_compeleceng_2024_109360 crossref_primary_10_3390_en15145260 crossref_primary_10_3390_en16041789 crossref_primary_10_1080_09398368_2017_1413161 crossref_primary_10_1109_TPWRD_2022_3183017 |
| Cites_doi | 10.1109/59.317683 10.1109/TPWRD.2006.874609 10.1109/TPWRD.2004.834677 10.1049/ip-c.1991.0060 10.1109/TPWRS.2011.2157539 10.1109/TPWRD.2003.813894 10.1109/TPAS.1981.316681 10.1016/j.ijepes.2012.07.070 10.1049/ip-gtd:20030943 10.1016/j.epsr.2011.03.019 10.1109/59.627847 10.1109/TPWRD.2012.2231966 10.1109/TPWRD.2008.2005682 10.1109/TPWRD.2013.2266513 10.1049/ip-c.1989.0048 10.1109/61.400869 10.1016/j.epsr.2013.09.010 |
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| Keywords | multilayer perceptrons artificial neural network phasor estimation method power system measurement power system protection numerical protective relay amplitude estimation performance evaluation power engineering computing phase estimation relay protection numerical analysis online training process electric current measurement multilayer perceptron structure current measurement DC offset decaying phasor measurement learning (artificial intelligence) phase angle estimation |
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Gener. Transm. Distrib. doi: 10.1049/ip-c.1991.0060 contributor: fullname: Eichhorn K.F. – volume: 26 start-page: 2336 issue: 4 year: 2011 ident: e_1_2_7_21_1 article-title: Instantaneous oscillating phasor estimates with TaylorK–Kalman filters publication-title: IEEE Trans. Power Syst. doi: 10.1109/TPWRS.2011.2157539 contributor: fullname: O Serna J.A. – start-page: 105 volume-title: The backpropagation algorithm applied to protective relaying year: 1997 ident: e_1_2_7_20_1 contributor: fullname: Coury D.V. – start-page: 489 volume-title: A joint frequency and phasor estimation algorithm using DFT samples for power systems year: 2013 ident: e_1_2_7_22_1 contributor: fullname: Fang L. – start-page: 1 volume-title: New modified algorithm to eliminate the effect of the DC offset on phasor estimation using DFT year: 2008 ident: e_1_2_7_2_1 contributor: fullname: Lee D. – ident: e_1_2_7_9_1 doi: 10.1109/TPWRD.2003.813894 – volume: 100 start-page: 3387 issue: 7 year: 1981 ident: e_1_2_7_11_1 article-title: Application of Kalman filtering in computer relaying publication-title: IEEE Trans. Power Appar. Syst. doi: 10.1109/TPAS.1981.316681 contributor: fullname: Girgis A.A. – volume: 44 start-page: 921 issue: 1 year: 2013 ident: e_1_2_7_27_1 article-title: Genetic algorithms applied to phasor estimation and frequency tracking in PMU development publication-title: Int. J. Electr. Power Energy Syst. doi: 10.1016/j.ijepes.2012.07.070 contributor: fullname: Silva R.P.M. – volume: 150 start-page: 745 issue: 6 year: 2003 ident: e_1_2_7_5_1 article-title: Discrete‐Fourier‐transform‐based technique for removal of decaying DC offset from phasor estimates publication-title: IEEE Proc. Gener. Transm. Distrib. doi: 10.1049/ip-gtd:20030943 contributor: fullname: Sidhu T.S. – start-page: 1 volume-title: A recursive least‐squares aided by pre‐filtering for phasor‐estimation in distance protection year: 2013 ident: e_1_2_7_24_1 contributor: fullname: Costa F.F. – volume: 81 start-page: 1627 issue: 7 year: 2011 ident: e_1_2_7_6_1 article-title: Online algorithm for removal of decaying DC‐offset from fault currents publication-title: Electr. Power Syst. Res. doi: 10.1016/j.epsr.2011.03.019 contributor: fullname: Al‐Tallaq K.N.A. – volume: 12 start-page: 1494 issue: 4 year: 1997 ident: e_1_2_7_19_1 article-title: Fast estimation of voltage and current phasors in power networks using an adaptive neural network publication-title: IEEE Trans. Power Syst. doi: 10.1109/59.627847 contributor: fullname: Dash P.K. – volume: 28 start-page: 807 issue: 2 year: 2013 ident: e_1_2_7_25_1 article-title: A new fast algorithm to estimate real‐time phasors using adaptive signal processing publication-title: IEEE Trans. Power Deliv. doi: 10.1109/TPWRD.2012.2231966 contributor: fullname: Abbas S.A. – ident: e_1_2_7_3_1 doi: 10.1109/TPWRD.2008.2005682 – volume: 28 start-page: 2172 issue: 4 year: 2013 ident: e_1_2_7_10_1 article-title: A new DFT‐based current phasor estimation for numerical protective relaying publication-title: IEEE Trans. Power Deliv. doi: 10.1109/TPWRD.2013.2266513 contributor: fullname: Zadeh M.R.D. – volume: 136 start-page: 347 issue: 6 year: 1991 ident: e_1_2_7_13_1 article-title: Nonrecursive methods for real‐time determination of basic waveforms of voltages and currents publication-title: IEEE Proc. Gener. Transm. Distrib. doi: 10.1049/ip-c.1989.0048 contributor: fullname: Lobos T. – start-page: 737 volume-title: Digital methods for online calculation of the basic components of signals in electrical power systems year: 1987 ident: e_1_2_7_12_1 contributor: fullname: Lobos T. – ident: e_1_2_7_15_1 doi: 10.1109/61.400869 – volume: 107 start-page: 109 year: 2014 ident: e_1_2_7_26_1 article-title: Programmable logic design of a compact genetic algorithm for phasor estimation in real‐time publication-title: Electr. Power Syst. Res. doi: 10.1016/j.epsr.2013.09.010 contributor: fullname: Coury D.V. |
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| SubjectTerms | Algorithms amplitude estimation artificial neural network current measurement DC offset decaying Devices electric current measurement learning (artificial intelligence) Mathematical models multilayer perceptron structure Multilayer perceptrons Neural networks numerical analysis numerical protective relay Online online training process performance evaluation phase angle estimation phase estimation phasor estimation method phasor measurement Phasors power engineering computing power system measurement power system protection relay protection Training |
| Title | Phasor estimation in power systems using a neural network with online training for numerical relays purposes |
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