A novel hybrid ensemble LSTM-FFNN forecasting model for very short-term and short-term PV generation forecasting
Datum
2022Language
en
Schlagwort
Zusammenfassung
The increasing penetration of photovoltaic (PV) systems into the electrical energy systems brings forward several technical and economic issues that mostly relate to their unpredictable nature. A promising solution to many of these is the implementation of robust PV generation forecasting models. In this paper a novel hybrid Ensemble Long Short-Term Memory-Feed Forward Neural Network (ELSTM-FFNN) model is proposed, that is able to perform both very-short and short-term forecasting. The performance of the proposed model is compared with individual LSTM models, and its forecasting accuracy is assessed in two different forecasting horizons: (a) 15-min ahead and (b) 1-h ahead. Moreover, in order to fully examine the contribution of the utilized data to the performance of the model, several scenarios have been formulated for each forecasting horizon. The results indicate that the proposed ELSTM-FFNN model can increase the forecasting accuracy in both horizons between 3–11.9% and 0.2–17.8%, respectively, considering the Mean Absolute Range Normalized Error (MARNE). © 2021 The Authors. IET Renewable Power Generation published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.
Collections
Verwandte Dokumente
Anzeige der Dokumente mit ähnlichem Titel, Autor, Urheber und Thema.
-
Combined forecasting system for short-term bus load forecasting based on clustering and neural networks
Panapakidis I.P., Skiadopoulos N., Christoforidis G.C. (2020)Micro-grids as 'micro-graphs' of the power systems involve the management of small loads, either isolated or connected to the main grid. Load forecasting is a tool of fundamental importance in power systems design and ... -
Optimized Data-Driven Models for Short-Term Electricity Price Forecasting Based on Signal Decomposition and Clustering Techniques
Arvanitidis A.I., Bargiotas D., Kontogiannis D., Fevgas A., Alamaniotis M. (2022)In recent decades, the traditional monopolistic energy exchange market has been replaced by deregulated, competitive marketplaces in which electricity may be purchased and sold at market prices like any other commodity. ... -
Forecasting Methods to Support the Decision Framework of Prosumers in Deregulated Markets
Panapakidis I.P., Koltsaklis N.E., Christoforidis G.C. (2021)In the present paper, a profit maximization problem for a prosumer is formulated and solved. The prosumer selects the electricity procurement approach among the pool market and forward contracts. Instead of treating the ...