Enhancing Power Quality and Grid Control with Real-Time Monitoring Sensors
Monitoring and controlling power quality is become crucial to ensure the power system runs steadily as smart grids have developed quickly. Issues related to conventional power quality monitoring techniques include insufficient real-time performance and limited monitoring accuracy. In order to increase real-time monitoring accuracy, this paper suggests smart grid reliability tracking and modification technique that employs photoelectric sensors combined optical systems signal treatment. In this article, the power grid's power quality is continuously monitored using photoelectric sensors, which then send information about the monitoring to an optical system. Key power quality metrics are extracted via signal processing of information collected via optical devices. Finally, the control and improvement of the quality of power can be achieved by making changes to the smart grid's important equipment. The tests show that using photoelectric sensors along with optical system processing to observe and change the power quality in a smart grid can make tracking more accurate and improve real-time performance. The power grid is much more stable and reliable now that it could be checked and managed at real time for changes in power quality.
Authors
- R. Senthamil Selvan (ORCID: https://orcid.org/0000-0002-2299-8890)
- R Pramodhini
- Dakka Obulesu (ORCID: https://orcid.org/0000-0001-6244-844X)
- D Preethi (ORCID: https://orcid.org/0000-0002-6603-5252)
- ParnandiBhaskar Rao
- M. Prabha (ORCID: https://orcid.org/0000-0002-0396-0037)
- Amitvikram C Nawalagatti
Institutions
- Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology (IN)
- Annamalai University (IN)
- Meenakshi Academy of Higher Education and Research (IN)
- CMR University (IN)
- Rural Resources (US)
- Aditya Birla (India) (IN)
Publication Details
- Journal
- Metallurgical and Materials Engineering
- Published
- 2025-01-22
- DOI
- https://doi.org/10.63278/1275
- Citations
- 1
- Primary Topic
- Smart Grid Energy Management
- Type
- article
- Field-Weighted Citation Impact
- 0.73