Data-Driven Techniques for Short-Term Electricity Price Forecasting through Novel Deep Learning Approaches with Attention Mechanisms

Data-Driven Techniques for Short-Term Electricity Price Forecasting through Novel Deep Learning Approaches with Attention Mechanisms

The electricity market is constantly evolving, being driven by factors such as market liberalization, the increasing use of renewable energy sources (RESs), and various economic and political influences. These dynamics make it challenging to predict wholesale electricity prices. Accurate short-term...

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Bibliographic Details
Main Authors: Vasileios Laitsos, Georgios Vontzos, Dimitrios Bargiotas, Aspassia Daskalopulu, Lefteri H. Tsoukalas
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Energies
Subjects:
load forecasting
long short-term memory
perceptron
convolutional neural networks (CNN)
Multi-Head Attention
transformer
Online Access:https://www.mdpi.com/1996-1073/17/7/1625

Internet

https://www.mdpi.com/1996-1073/17/7/1625

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