The importance of renewable energy sources has been increasing in recent years due to the advantages they provide, in terms of the preservation of the environment and inexhaustible supply of energy. In particular, photovoltaic (PV) energy will be prioritized in the future and it is expanding worldwide. However, the high variability of solar irradiance and, consequently, of PV power generation causes uncertainty in the planning and operation of power systems. Thus, PV power generation forecasting is crucial to solve this issue. This paper presents the comparison of LSTM-based methods for the 6-hour-ahead and day-ahead forecasting of PV power generated by a PV power station, based on the Global Horizontal Irradiance and the air temperature forecasts of the same period.

Comparison of LSTM-Based Models for the 6-Hour-Ahead and Day-Ahead Forecasting of Photovoltaic Power Generation / Ghione, G.; Randazzo, V.; Pasero, E.; Badami, M. (SMART INNOVATION, SYSTEMS AND TECHNOLOGIES). - In: Smart Innovation, Systems and Technologies / Esposito A., Faundez-Zanuy M., Morabito F. C., Pasero E., Cordasco G.. - STAMPA. - Singapore : Springer Nature, 2025. - ISBN 9789819609932. - pp. 45-54 [10.1007/978-981-96-0994-9_5]

Comparison of LSTM-Based Models for the 6-Hour-Ahead and Day-Ahead Forecasting of Photovoltaic Power Generation

Ghione G.;Randazzo V.;Pasero E.;Badami M.
2025

Abstract

The importance of renewable energy sources has been increasing in recent years due to the advantages they provide, in terms of the preservation of the environment and inexhaustible supply of energy. In particular, photovoltaic (PV) energy will be prioritized in the future and it is expanding worldwide. However, the high variability of solar irradiance and, consequently, of PV power generation causes uncertainty in the planning and operation of power systems. Thus, PV power generation forecasting is crucial to solve this issue. This paper presents the comparison of LSTM-based methods for the 6-hour-ahead and day-ahead forecasting of PV power generated by a PV power station, based on the Global Horizontal Irradiance and the air temperature forecasts of the same period.
2025
9789819609932
9789819609949
Smart Innovation, Systems and Technologies
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/3002110