Forecast combinations: An over 50-year review

X Wang, RJ Hyndman, F Li, Y Kang - International Journal of Forecasting, 2023 - Elsevier
Forecast combinations have flourished remarkably in the forecasting community and, in
recent years, have become part of mainstream forecasting research and activities …

Energy forecasting: A review and outlook

T Hong, P Pinson, Y Wang, R Weron… - IEEE Open Access …, 2020 - ieeexplore.ieee.org
Forecasting has been an essential part of the power and energy industry. Researchers and
practitioners have contributed thousands of papers on forecasting electricity demand and …

Electricity price forecasting on the day-ahead market using machine learning

L Tschora, E Pierre, M Plantevit, C Robardet - Applied Energy, 2022 - Elsevier
The price of electricity on the European market is very volatile. This is due both to its mode of
production by different sources, each with its own constraints (volume of production …

[HTML][HTML] Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark

J Lago, G Marcjasz, B De Schutter, R Weron - Applied Energy, 2021 - Elsevier
While the field of electricity price forecasting has benefited from plenty of contributions in the
last two decades, it arguably lacks a rigorous approach to evaluating new predictive …

Neural basis expansion analysis with exogenous variables: Forecasting electricity prices with NBEATSx

KG Olivares, C Challu, G Marcjasz, R Weron… - International Journal of …, 2023 - Elsevier
We extend neural basis expansion analysis (NBEATS) to incorporate exogenous factors.
The resulting method, called NBEATSx, improves on a well-performing deep learning …

[HTML][HTML] Forecasting spot electricity prices: Deep learning approaches and empirical comparison of traditional algorithms

J Lago, F De Ridder, B De Schutter - Applied Energy, 2018 - Elsevier
In this paper, a novel modeling framework for forecasting electricity prices is proposed.
While many predictive models have been already proposed to perform this task, the area of …

Recent advances in electricity price forecasting: A review of probabilistic forecasting

J Nowotarski, R Weron - Renewable and Sustainable Energy Reviews, 2018 - Elsevier
Since the inception of competitive power markets two decades ago, electricity price
forecasting (EPF) has gradually become a fundamental process for energy companies' …

[HTML][HTML] Electricity price forecasting: A review of the state-of-the-art with a look into the future

R Weron - International journal of forecasting, 2014 - Elsevier
A variety of methods and ideas have been tried for electricity price forecasting (EPF) over the
last 15 years, with varying degrees of success. This review article aims to explain the …

Effective long short-term memory with differential evolution algorithm for electricity price prediction

L Peng, S Liu, R Liu, L Wang - Energy, 2018 - Elsevier
Electric power, as an efficient and clean energy, has considerable importance in industries
and human lives. Electricity price is becoming increasingly crucial for balancing electricity …

[HTML][HTML] China mainland new energy index price forecasting with the neural network

X Xu, Y Zhang - Energy Nexus, 2023 - Elsevier
For policymakers and investors, forecasting prices of energy indices has always been an
important task. The present work focuses on the Chinese market and explores the daily price …