Analysis and Modeling for Short- to Medium-Term Load Forecasting Using a Hybrid Manifold Learning Principal Component Model and Comparison with Classical Statistical Models (SARIMAX, Exponential Smoothing) and Artificial Intelligence Models (ANN, SVM): The Case of Greek Electricity Market

Analysis and Modeling for Short- to Medium-Term Load Forecasting Using a Hybrid Manifold Learning Principal Component Model and Comparison with Classical Statistical Models (SARIMAX, Exponential Smoothing) and Artificial Intelligence Models (ANN, SVM): The Case of Greek Electricity Market

In this work we propose a new hybrid model, a combination of the manifold learning Principal Components (PC) technique and the traditional multiple regression (PC-regression), for short and medium-term forecasting of daily, aggregated, day-ahead, electricity system-wide load in the Greek Electricity...

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Bibliographic Details
Main Authors: George P. Papaioannou, Christos Dikaiakos, Anargyros Dramountanis, Panagiotis G. Papaioannou
Format: Article
Language:English
Published: MDPI AG 2016-08-01
Series:Energies
Subjects:
forecasting
electricity load
exponential smoothing
seasonal autoregressive integrated moving average with exogenous (SARIMAX)
principal components analysis
Online Access:http://www.mdpi.com/1996-1073/9/8/635

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