Smart Maintenance with Regression Analysis for Efficiency Improvement in Photovoltaic Energy Systems

Document Type : Original Article

Authors

1 Department of Alternative Energy Resources Technology Program, Hacettepe Ankara Chamber of Industry 1st Organized Industrial Zone Vocational School, Hacettepe University, Ankara, Türkiye

2 Department of Computer Engineering, Faculty of Engineering and Natural Sciences, Kırıkkale University, Kırıkkale, Türkiye.

3 National Technical University of Athens, Athens, Greece

4 North West Regional College, Londonderry, Northern Ireland

5 Sincan District Directorate of National Education, Ankara, Türkiye

6 Impektra IT Software, Ankara, Türkiye

7 Yenikent Ahmet Çiçek Vocational and Technical Anatolian High School, Ankara, Türkiye

8 Private Ankara Chamber of Industry Technical College Vocational and Technical Anatolian High School, Ankara, Türkiye

9 Ankara Chamber of Industry 1st Organized Industrial Zone Management, Ankara, Türkiye

10 Oryx-Data Incubator EURL, Paris, France

10.22059/jser.2023.363200.1335

Abstract

This research had the overarching goal of optimizing maintenance intervals and reducing the maintenance workload by enhancing accessibility for individuals lacking technical expertise in the upkeep of photovoltaic systems, with a particular focus on rooftop applications. The study achieved this objective by employing a linear regression algorithm to analyse climatic parameters such as wind speed, humidity, ambient temperature, and light intensity, collected from the installation site of a photovoltaic solar energy system. Simultaneously, the current and voltage values obtained from the system were also examined. This analysis not only facilitated the determination of power generation within the system but also enabled real-time detection of potential issues such as pollution, shadowing, bypass, and panel faults on the solar panels. Additionally, an artificial intelligence-supported interface was developed within the study, attributing any decline in power generation to specific causes and facilitating prompt intervention to rectify malfunctions, thereby ensuring more efficient system operation.

Keywords

References

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Journal of Solar Energy Research
Volume 8, Issue 4
October 2023
Pages 1663-1679

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