<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper lays the foundation for the subsequent analysis of power quality in distribution networks by briefly describing the indicators of power quality. Utilizing the zero sequence voltage mutation detection fault of a small current routing algorithm, the instantaneous values of voltage and current of each phase of the three-phase circuit are quickly calculated based on the electrical parameters of instantaneous reactive power and the online intelligent detection system is established. The effectiveness and feasibility of the designed detection system and detection algorithm in detecting electrical energy parameters have been verified through experiments. The results show that the error of voltage measurement is within 0.0003-0.002, the frequency error of the system is up to 0.0117%, the measurement error of three-phase unbalance is distributed between 0.001 and 0.1, and the error of negative sequence and zero sequence is between ±0.003, which meet the system design requirements. It shows that the use of online intelligent detection systems can improve the quality of distribution network operation and fault identification accuracy, improve power quality, and effectively improve the reliability of power supply.</p>
</abstract>

This paper lays the foundation for the subsequent analysis of power quality in distribution networks by briefly describing the indicators of power quality. Utilizing the zero sequence voltage mutation detection fault of a small current routing algorithm, the instantaneous values of voltage and current of each phase of the three-phase circuit are quickly calculated based on the electrical parameters of instantaneous reactive power and the online intelligent detection system is established. The effectiveness and feasibility of the designed detection system and detection algorithm in detecting electrical energy parameters have been verified through experiments. The results show that the error of voltage measurement is within 0.0003-0.002, the frequency error of the system is up to 0.0117%, the measurement error of three-phase unbalance is distributed between 0.001 and 0.1, and the error of negative sequence and zero sequence is between ±0.003, which meet the system design requirements. It shows that the use of online intelligent detection systems can improve the quality of distribution network operation and fault identification accuracy, improve power quality, and effectively improve the reliability of power supply.

Design of Online Intelligent Detection System for Power Quality and Fault Identification in Distribution Networks

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper lays the foundation for the subsequent analysis of power quality in distribution networks by briefly describing the indicators of power quality....

Design of Online Intelligent Detection System for Power Quality and Fault Identification in Distribution Networks

Publié en ligne: 13 déc. 2023

Pages: -

Reçu: 21 févr. 2023

Accepté: 23 juin 2023

DOI: https://doi.org/10.2478/amns.2023.2.01454

Mots clés
Power quality, Three-phase unbalance, Small current line selection, Instantaneous reactive power, Intelligent detection system

© 2023 Wanru He et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Design of Online Intelligent Detection System for Power Quality and Fault Identification in Distribution Networks

Publié en ligne: 13 déc. 2023

Pages: -

Reçu: 21 févr. 2023

Accepté: 23 juin 2023

DOI: https://doi.org/10.2478/amns.2023.2.01454

Mots clésPower quality, Three-phase unbalance, Small current line selection, Instantaneous reactive power, Intelligent detection system

© 2023 Wanru He et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
Power quality, Three-phase unbalance, Small current line selection, Instantaneous reactive power, Intelligent detection system