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Forecasting electricity prices from the state-of-the-art modeling technology and the price determinant perspectives
S Chai, Q Li, MZ Abedin, BM Lucey - Research in International Business …, 2024 - Elsevier
Accurate electricity price forecasting (EPF) is crucial to participants and decision-makers
within the electricity market. This paper reviews 62 screened literature works on EPF during …
within the electricity market. This paper reviews 62 screened literature works on EPF during …
[HTML][HTML] Predictive modelling for solar thermal energy systems: A comparison of support vector regression, random forest, extra trees and regression trees
Predictive analytics play an important role in the management of decentralised energy
systems. Prediction models of uncontrolled variables (eg, renewable energy sources …
systems. Prediction models of uncontrolled variables (eg, renewable energy sources …
[HTML][HTML] Electricity price forecasting using recurrent neural networks
Accurate electricity price forecasting has become a substantial requirement since the
liberalization of the electricity markets. Due to the challenging nature of electricity prices …
liberalization of the electricity markets. Due to the challenging nature of electricity prices …
An electricity price forecasting model by hybrid structured deep neural networks
Electricity price is a key influencer in the electricity market. Electricity market trades by each
participant are based on electricity price. The electricity price adjusted with the change in …
participant are based on electricity price. The electricity price adjusted with the change in …
Forecasting day-ahead electricity prices: A comparison of time series and neural network models taking external regressors into account
The amount of renewable energies in electricity production has increased significantly in the
last decade, resulting in more variability of the day-ahead electricity spot price. The …
last decade, resulting in more variability of the day-ahead electricity spot price. The …
An optimized heterogeneous structure LSTM network for electricity price forecasting
Electricity price is an important indicator of the market operation. Accurate prediction of
electricity price will facilitate the maximization of economic benefits and reduction of risks to …
electricity price will facilitate the maximization of economic benefits and reduction of risks to …
Electricity spot prices forecasting based on ensemble learning
Efficient modeling and forecasting of electricity prices are essential in today's competitive
electricity markets. However, price forecasting is not easy due to the specific features of the …
electricity markets. However, price forecasting is not easy due to the specific features of the …
On the importance of the long-term seasonal component in day-ahead electricity price forecasting with NARX neural networks
Daily and weekly seasonalities are always taken into account in day-ahead electricity price
forecasting, but the long-term seasonal component has long been believed to add …
forecasting, but the long-term seasonal component has long been believed to add …
[HTML][HTML] Electricity price forecasting in the irish balancing market
Short-term electricity markets are becoming more relevant due to less-predictable
renewable energy sources, attracting considerable attention from the industry. The …
renewable energy sources, attracting considerable attention from the industry. The …
[HTML][HTML] Selection of calibration windows for day-ahead electricity price forecasting
We conduct an extensive empirical study on the selection of calibration windows for day-
ahead electricity price forecasting, which involves six year-long datasets from three major …
ahead electricity price forecasting, which involves six year-long datasets from three major …