Energy consumption forecast in peer to peer energy trading

Energy consumption forecast in peer to peer energy trading

Abstract This study predicts future values of energy consumption demand from a novel dataset that includes the energy consumption during COVID-19 lockdown, using up-to-date deep learning algorithms to reduce peer-to-peer energy system losses and congestion. Three learning algorithms, namely Random F...

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Bibliographic Details
Main Authors: Hend G. Hassan, Ahmed A. Shahin, Ibrahim E. Ziedan
Format: Article
Language:English
Published: Springer 2023-07-01
Series:SN Applied Sciences
Subjects:
Blockchain
P2p energy trading
Random forest
Bi-LSTM
GRU
Prediction
Online Access:https://doi.org/10.1007/s42452-023-05424-6

Internet

https://doi.org/10.1007/s42452-023-05424-6

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