Bibliographic Details
| Title: |
Assessing power quality in individual circuits of industrial electrical system. |
| Authors: |
Angarita, Eliana Noriega1 enoriega2@cuc.edu.co, Santos, Vladimir Sousa1 vsousa1@cuc.edu.co, Donolo, Pablo Daniel2 pdonolo@ing.unrc.edu.ar, Quispe, Enrique Ciro3 ecquispe@uao.edu.co |
| Source: |
International Journal of Electrical & Computer Engineering (2088-8708). Oct2024, Vol. 14 Issue 5, p4888-4896. 9p. |
| Subjects: |
Industrialism, Electrical load, Energy dissipation, Power transformers, Electric circuits |
| Abstract: |
This article evaluates energy quality in individual circuits within an industrial electrical system and its impact on common connection point parameters. The research is crucial due to rising challenges in power quality arising from increased nonlinear electrical loads in industrial processes. The study involves sequential steps, covering the industrial electrical system's description, power quality parameters analysis, and issue identification. A comprehensive assessment was conducted on a 3,000 kVA, 13.8 kV/460 V point of common coupling (PCC) transformer, and 10 transformers (10 to 250 kVA) supplying individual circuits. Findings indicated load factors below 70% in all transformers and a power factor below 0.9 in eight. Issues like voltage variation, current imbalance, and harmonic distortion were identified in nine transformers supplying individual circuits, while the PCC exhibited no power quality problems. The research emphasizes the importance of including individual circuits in power quality assessments, as compliance with regulatory limits at the PCC may not guarantee the absence of power quality issues in individual circuits, affecting equipment lifespan and increasing energy losses. [ABSTRACT FROM AUTHOR] |
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Copyright of International Journal of Electrical & Computer Engineering (2088-8708) is the property of Institute of Advanced Engineering & Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Engineering Source |