An Algorithm for Circuit Parameter Identification in Lightning Impulse Voltage Generation for Low-Inductance Loads
This paper presents an effective technique based on an artificial neural network algorithm utilized for circuit parameter identification in lightning impulse generation for low inductance loads such as low voltage windings of a power transformer, a large distribution transformer and an air core reac...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-07-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/13/15/3913 |
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| author | Piyapon Tuethong Krit Kitwattana Peerawut Yutthagowith Anantawat Kunakorn |
| author_facet | Piyapon Tuethong Krit Kitwattana Peerawut Yutthagowith Anantawat Kunakorn |
| author_sort | Piyapon Tuethong |
| collection | DOAJ |
| description | This paper presents an effective technique based on an artificial neural network algorithm utilized for circuit parameter identification in lightning impulse generation for low inductance loads such as low voltage windings of a power transformer, a large distribution transformer and an air core reactor. The limitation of the combination between Glaninger’s circuit and the circuit parameter selection from Feser’s suggestions in term of producing an impulse waveform to be compliant with standard requirements when working with a low inductance load is discussed. In Feser’s approach, the circuit parameters of the generation circuit need to be further adjusted to obtain the waveform compliant with the standard requirement. In this process, trial and error approaches based on test engineers’ experience are employed in the circuit parameter selection. To avoid the unintentional damage from electrical field stress during the voltage waveform adjustment process, circuit simulators, such as Pspice and EMTP/ATP, are very useful to examine the generated voltage waveform before the experiments on the test object are carried out. In this paper, a system parameter identification based on an artificial neural network algorithm is applied to determine the appropriate circuit parameters in the test circuit. This impulse voltage generation with the selected circuit parameters was verified by simulations and an experiment. It was found that the generation circuit gives satisfactory impulse voltage waveforms in accordance with the standard requirement for the maximum charging capacitance of 10 µF and the load inductance from 400 µH to 4 mH. From the simulation and experimental results of all cases, the approach proposed in this paper is useful for test engineers in selection of appropriate circuit components for impulse voltage tests with low inductance loads instead of employing conventional trial and error in circuit component selection. |
| first_indexed | 2024-03-10T18:04:39Z |
| format | Article |
| id | doaj.art-daa06bd9ce7b4f3f99b2527557aab10b |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T18:04:39Z |
| publishDate | 2020-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-daa06bd9ce7b4f3f99b2527557aab10b2023-11-20T08:38:20ZengMDPI AGEnergies1996-10732020-07-011315391310.3390/en13153913An Algorithm for Circuit Parameter Identification in Lightning Impulse Voltage Generation for Low-Inductance LoadsPiyapon Tuethong0Krit Kitwattana1Peerawut Yutthagowith2Anantawat Kunakorn3Faculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, ThailandFaculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, ThailandFaculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, ThailandFaculty of Engineering, King Mongkut’s Institute of Technology Ladkrabang, Bangkok 10520, ThailandThis paper presents an effective technique based on an artificial neural network algorithm utilized for circuit parameter identification in lightning impulse generation for low inductance loads such as low voltage windings of a power transformer, a large distribution transformer and an air core reactor. The limitation of the combination between Glaninger’s circuit and the circuit parameter selection from Feser’s suggestions in term of producing an impulse waveform to be compliant with standard requirements when working with a low inductance load is discussed. In Feser’s approach, the circuit parameters of the generation circuit need to be further adjusted to obtain the waveform compliant with the standard requirement. In this process, trial and error approaches based on test engineers’ experience are employed in the circuit parameter selection. To avoid the unintentional damage from electrical field stress during the voltage waveform adjustment process, circuit simulators, such as Pspice and EMTP/ATP, are very useful to examine the generated voltage waveform before the experiments on the test object are carried out. In this paper, a system parameter identification based on an artificial neural network algorithm is applied to determine the appropriate circuit parameters in the test circuit. This impulse voltage generation with the selected circuit parameters was verified by simulations and an experiment. It was found that the generation circuit gives satisfactory impulse voltage waveforms in accordance with the standard requirement for the maximum charging capacitance of 10 µF and the load inductance from 400 µH to 4 mH. From the simulation and experimental results of all cases, the approach proposed in this paper is useful for test engineers in selection of appropriate circuit components for impulse voltage tests with low inductance loads instead of employing conventional trial and error in circuit component selection.https://www.mdpi.com/1996-1073/13/15/3913artificial neural networkcircuit designGlaninger circuitlightning impulse voltage testslow inductance loadssystem parameter identification |
| spellingShingle | Piyapon Tuethong Krit Kitwattana Peerawut Yutthagowith Anantawat Kunakorn An Algorithm for Circuit Parameter Identification in Lightning Impulse Voltage Generation for Low-Inductance Loads Energies artificial neural network circuit design Glaninger circuit lightning impulse voltage tests low inductance loads system parameter identification |
| title | An Algorithm for Circuit Parameter Identification in Lightning Impulse Voltage Generation for Low-Inductance Loads |
| title_full | An Algorithm for Circuit Parameter Identification in Lightning Impulse Voltage Generation for Low-Inductance Loads |
| title_fullStr | An Algorithm for Circuit Parameter Identification in Lightning Impulse Voltage Generation for Low-Inductance Loads |
| title_full_unstemmed | An Algorithm for Circuit Parameter Identification in Lightning Impulse Voltage Generation for Low-Inductance Loads |
| title_short | An Algorithm for Circuit Parameter Identification in Lightning Impulse Voltage Generation for Low-Inductance Loads |
| title_sort | algorithm for circuit parameter identification in lightning impulse voltage generation for low inductance loads |
| topic | artificial neural network circuit design Glaninger circuit lightning impulse voltage tests low inductance loads system parameter identification |
| url | https://www.mdpi.com/1996-1073/13/15/3913 |
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