Power Demand Forecasting using Long Short-Term Memory (LSTM) Deep-Learning Model for Monitoring Energy Sustainability

Power Demand Forecasting using Long Short-Term Memory (LSTM) Deep-Learning Model for Monitoring Energy Sustainability

The purpose of this study is to design a novel custom power demand forecasting algorithm based on the LSTM Deep-Learning method regarding the recent power demand patterns. We performed tests to verify the error rates of the forecasting module, and to confirm the sudden change of power patterns in th...

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Bibliographic Details
Main Authors: Eunjeong Choi, Soohwan Cho, Dong Keun Kim
Format: Article
Language:English
Published: MDPI AG 2020-02-01
Series:Sustainability
Subjects:
short-term
seasonal forecasting
power demand forecasting
deep-learning
lstm
smart grid
power usage patterns
Online Access:https://www.mdpi.com/2071-1050/12/3/1109

Internet

https://www.mdpi.com/2071-1050/12/3/1109

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