The accurate forecasting of electricity price and load is essential for maintaining a stable interplay between demand and supply in the dynamic electricity market. In this work we propose a deep Convolutional Neural Network-based model for day-ahead electricity price forecasting from historical price/load data and predicted load values. The model was tested on the data for New York and New South Wales and demonstrated high prediction accuracy for both datasets.



Previziunea exactă a prețului și încărcării energiei electrice este esențială pentru menținerea unei interacțiuni stabile între cerere și ofertă pe piața dinamică a energiei electrice. În articol este descris un model profund bazat pe rețeaua neuronală convoluțională pentru prognozele viitoare ale prețului energiei electrice din datele istorice ale prețului / tarifelor și valorile prognozate ale tarifelor. Modelul a fost testat pe datele pentru New York și New South Wales și a demonstrat o precizie ridicată a predicțiilor pentru ambele seturi de date.


Deep Learning, Machine Learning, Long-Short Term Memory Networks, Convolutional Neural Networks.

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