The Influence of Pre-processing of Input Data on the Quality of Energy Yield Forecasts from a Photovoltaic Plant

Krzysztof Nęcka , Anna Karbowniczak , Hubert Latała , Marek Wróbel , Natalia Mioduszewska


The aim of this study was to analyse the influence of different methods of pre-processing of input data such as moving average, subtraction of the mean and smoothing with the 4253H filter on the quality of forecasts of energy yield from a photovoltaic plant developed on the basis of MLP artificial neural networks. Forecasts were conducted at hourly time intervals for three types of cells; mon- and polycrystalline cells, as well as CIGS thin-film cells. The aim of the study was achieved based on the authors’ own research conducted at a PV plant located in Krakow with a total power output of 12.67 kWp. The assessments of the models developed were made based on the total ratio of energy for balancing in the total energy production (ΔESR) and on an analysis of the mean absolute percentage error (MAPE).
Author Krzysztof Nęcka (FoPaPE / Department of Bioprocess Engineering, Power Engineering and Automation)
Krzysztof Nęcka,,
- Department of Bioprocess Engineering, Power Engineering and Automation
, Anna Karbowniczak (FoPaPE / IoAEaI)
Anna Karbowniczak,,
- Institute of Agricultural Engineering and Informatics
, Hubert Latała (FoPaPE / Department of Bioprocess Engineering, Power Engineering and Automation)
Hubert Latała,,
- Department of Bioprocess Engineering, Power Engineering and Automation
, Marek Wróbel (FoPaPE / DoMEaA)
Marek Wróbel,,
- Department of Mechanical Engineering and Agrophysics
, Natalia Mioduszewska - [Uniwersytet Przyrodniczy w Poznaniu]
Natalia Mioduszewska,,
- Uniwersytet Przyrodniczy w Poznaniu
Publication size in sheets0.5
Book Wróbel Marek, Jewiarz Marcin, Szlęk Andrzej (eds.): Renewable Energy Sources: Engineering, Technology, Innovation : ICORES 2018, Springer Proceedings in Energy, 2020, Springer, ISBN 978-3-030-13887-5, [978-3-030-13888-2], 1094 p., DOI:10.1007/978-3-030-13888-2
Keywords in EnglishModelling, Forecasting, Pre-processing, Photovoltaic cells
Languageen angielski
Score (nominal)20
Score sourcepublisherList
Citation count*
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FinansowanieThis research was financed by the Ministry of Science and Higher Education of the Republic of Poland.
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