A combination of weather clustering and data-driven methods for intraday PV power production forecasting
Date
2023Source
7th International Conference on Renewable Energy Sources and Energy Efficiency (RESEE 2023)Google Scholar check
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PV systems are becoming the primary solution for meeting future electricity demands as conventional power generation declines globally. However, integrating PV systems into distribution networks presents new challenges in maintaining continuous service during supply and demand fluctuations. To address these challenges, a new intraday PV production forecasting methodology is proposed for predicting production 1 to 3 hours ahead. The methodology involves data quality assessment, weather clustering, and machine learning modeling. The proposed methodology demonstrated errors below the 5% theoretical threshold.
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- Τμήμα Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών / Department of Electrical and Computer Engineering [2897]
- Κέντρο Aριστείας για Έρευνα και Καινοτομία σε Ευφυείς, Αποδοτικές και Βιώσιμες Ενεργειακές Λύσεις «ΦΑΕΘΩΝ» / PHAETHON Research and Innovation Centre of Excellence for Intelligent, Efficient and Sustainable Energy Solutions [32]