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Smart Maintenance with Regression Analysis for Efficiency Improvement in Photovoltaic Energy Systems | ||
| Journal of Solar Energy Research | ||
| دوره 8، شماره 4، دی 2023، صفحه 1663-1679 اصل مقاله (1.43 M) | ||
| نوع مقاله: Original Article | ||
| شناسه دیجیتال (DOI): 10.22059/jser.2023.363200.1335 | ||
| نویسندگان | ||
| İlker Ay1؛ Murat Kademli1؛ Serkan Savaş* 2؛ Sotirios Karellas3؛ Angelos Markopoulos3؛ Christina-Stavroula Hatzilau3؛ Philip Devlin4؛ Hüseyin Duşbudak5؛ Ali Samet Arslan6؛ Mustafa Koç7؛ Kazım Duraklar8؛ Kamil Sunal9؛ Mathieu Mehmet Ozer10 | ||
| 1Department of Alternative Energy Resources Technology Program, Hacettepe Ankara Chamber of Industry 1st Organized Industrial Zone Vocational School, Hacettepe University, Ankara, Türkiye | ||
| 2Department of Computer Engineering, Faculty of Engineering and Natural Sciences, Kırıkkale University, Kırıkkale, Türkiye. | ||
| 3National Technical University of Athens, Athens, Greece | ||
| 4North West Regional College, Londonderry, Northern Ireland | ||
| 5Sincan District Directorate of National Education, Ankara, Türkiye | ||
| 6Impektra IT Software, Ankara, Türkiye | ||
| 7Yenikent Ahmet Çiçek Vocational and Technical Anatolian High School, Ankara, Türkiye | ||
| 8Private Ankara Chamber of Industry Technical College Vocational and Technical Anatolian High School, Ankara, Türkiye | ||
| 9Ankara Chamber of Industry 1st Organized Industrial Zone Management, Ankara, Türkiye | ||
| 10Oryx-Data Incubator EURL, Paris, France | ||
| چکیده | ||
| 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. | ||
| کلیدواژهها | ||
| Photovoltaic؛ Efficiency؛ Solar energy system؛ Maintenance and repair؛ Regression analysis | ||
| مراجع | ||
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