Methods for the classification of harmonic distortion sources for nonlinear power system loads: a critical review
This paper demonstrates the method available for estimating the impacts of multiple nonlinear loads on current harmonics and voltage harmonics in the electrical network. In the power distribution system, there are standards such as IEEE519 which provide the guidelines for controlling the harmonic le...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Penerbit UTM Press
2021
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/98321/1/HermanWahid2021_MethodsfortheClassificationofHarmonicDistortion.pdf http://eprints.utm.my/id/eprint/98321/ https://elektrika.utm.my/index.php/ELEKTRIKA_Journal/article/view/331 |
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| Institution: | Universiti Teknologi Malaysia |
| Language: | English |
| Summary: | This paper demonstrates the method available for estimating the impacts of multiple nonlinear loads on current harmonics and voltage harmonics in the electrical network. In the power distribution system, there are standards such as IEEE519 which provide the guidelines for controlling the harmonic levels that give an isolated indicator between utility segment and customer. To ensure the utility voltage distortion at the point of common coupling (PCC), the customer needs to maintain the TDD percentage so that it does not impact the utility distribution system. Nevertheless, there is a possibility for a dispute between utilities and customers regarding who contributes the harmonic distortion to the PCC. This research will address the direction of harmonic source based on the proposed method and verify the output percentage of THD and TDD with reference to IEEE519 standards. There are two modelling schemes introduced in this review which are load modelling and source modelling using the neural network technique. The load modelling is a scheme to predict the current distortion. The source modelling is a scheme to predict the voltage distortion at the PCC. These two methods will operate at customer side as an automatic standalone tool without disrupting the operation of customer’s system. Customers will easily monitor the predicted current distortion in the system by the proposed method which internally runs the neural network algorithm. The utility company can penalize the customer based on the load modelling scheme. The proposed load and source modelling will give some idea on the harmonic filtering method. |
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