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A dynamic data-driven forecast prediction methodology for photovoltaic power systems |
Tartalom: | http://real.mtak.hu/120057/ |
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Archívum: | REAL |
Gyűjtemény: |
Status = Published
Subject = Q Science / természettudomány: QE Geology / földtudományok: QE04 Meteorology / meteorológia Type = Article |
Cím: |
A dynamic data-driven forecast prediction methodology for photovoltaic power systems
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Létrehozó: |
Kapros, Zoltán
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Kiadó: |
Országos Meteorológiai Szolgálat
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Dátum: |
2018
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Téma: |
QE04 Meteorology / meteorológia
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Tartalmi leírás: |
At present, the capacity of the new photovoltaic (PV) systems are growing rapidly in Hungary. The limit to growth can be estimated, but it is influenced by several things. Even a realistic goal for the next 20–30 years can be to reach the 20–25% variable renewable energy ratio in the electricity consumption. The main barrier is the variability of these systems, thus the grid integration is a huge challenge in the near future. A new dynamic data-driven forecasting methodology is worked out and tested by examining the Budapest District Heating Co. Ltd. top installed solar systems. The tested prediction method was only for 5 minutes ahead in the expected average performance in a 15-minute period. The main elements of the tested methodology and some main results will be presented in this article.
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Nyelv: |
angol
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Típus: |
Article
PeerReviewed
info:eu-repo/semantics/article
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Formátum: |
text
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Azonosító: |
Kapros, Zoltán (2018) A dynamic data-driven forecast prediction methodology for photovoltaic power systems. IDŐJÁRÁS / QUARTERLY JOURNAL OF THE HUNGARIAN METEOROLOGICAL SERVICE, 122 (3). pp. 345-360. ISSN 0324-6329
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Kapcsolat: |
MTMT:3418391 10.28974/idojaras.2018.3.7
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