Optimized Data-Driven Models for Short-Term Electricity Price Forecasting Based on Signal Decomposition and Clustering Techniques

Optimized Data-Driven Models for Short-Term Electricity Price Forecasting Based on Signal Decomposition and Clustering Techniques

In recent decades, the traditional monopolistic energy exchange market has been replaced by deregulated, competitive marketplaces in which electricity may be purchased and sold at market prices like any other commodity. As a result, the deregulation of the electricity industry has produced a demand...

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Bibliographic Details
Main Authors: Athanasios Ioannis Arvanitidis, Dimitrios Bargiotas, Dimitrios Kontogiannis, Athanasios Fevgas, Miltiadis Alamaniotis
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Energies
Subjects:
short-term electricity price forecasting
data-driven forecasting models
metaheuristic optimization algorithms
signal decomposition
clustering algorithms
preprocessing approaches
Online Access:https://www.mdpi.com/1996-1073/15/21/7929

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