Spremljeno u:
| Glavni autori: | , |
|---|---|
| Format: | Recurso digital |
| Jezik: | engleski |
| Izdano: |
Zenodo
2026
|
| Teme: | |
| Online pristup: | https://doi.org/10.5281/zenodo.18917878 |
| Oznake: |
Dodaj oznaku
Bez oznaka, Budi prvi tko označuje ovaj zapis!
|
Sadržaj:
- <p>Abstract<br>Power factor correction remains a significant challenge in modern industrial power systems due to the presence <br>of highly inductive and fluctuating loads. Poor power factor results in increased energy losses, reduced system <br>efficiency, and higher operational costs. Conventional correction methods based on mechanical or thyristor <br>switching provide limited intelligence and slower adaptability to dynamic load variations. This paper presents <br>the design and hardware implementation of an Edge AI-driven IoT framework for automatic power factor <br>correction in smart industrial environments. The proposed system utilizes voltage and current sensing modules <br>integrated with an ESP8266 controller to continuously monitor electrical parameters. Edge Artificial <br>Intelligence enables real-time local decision-making for optimal capacitor bank switching to compensate <br>reactive power effectively. IoT connectivity allows remote monitoring and data visualization through cloud <br>platforms. The developed system maintains near-unity power factor, minimizes harmonics, and optimizes <br>current consumption under varying load conditions. Experimental results demonstrate improved power quality, <br>faster response time, and enhanced energy efficiency compared to conventional APFC systems.</p>