Forecasting Day-Ahead Electricity Demand in Australia Using a CNN-LSTM Model with an Attention Mechanism

Forecasting Day-Ahead Electricity Demand in Australia Using a CNN-LSTM Model with an Attention Mechanism

Accurate energy demand forecasting is vital for optimizing resource allocation and energy efficiency. Despite advancements in various prediction models, existing approaches often struggle to capture the complex, nonlinear relationships between temperature variations and electricity consumption. To a...

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Bibliographic Details
Main Authors: Laial Alsmadi, Gang Lei, Li Li
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Applied Sciences
Subjects:
electricity demand
prediction
heating degree days
cooling degree days
deep learning
Convolutional Neural Network (CNN)
Online Access:https://www.mdpi.com/2076-3417/15/7/3829
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