Forecasting Renewable Energy at European Markets
Additional information
Authors
Rim H.,
Schenk O.,
Kardoš J.,
for Computing Machinery A.
Type
Article in conference proceedings
Year
2025
Language
English
Abstract
The ambitious energy targets, accelerated by the recent energy crisis, are driving the increase of renewable energy share in gross energy consumption. However, the intermittent and seasonal nature of renewable energy sources presents challenges in predicting their production capacity. The ability to accurately forecast the evolution of renewable energy’s stake in the dynamic and ever-evolving energy market is a critical component in the decision making process of policy makers, and market participants alike. This project aims to explore and evaluate the performance of well-established forecasting methods in anticipating the trends of individual renewable energy components, ultimately contributing to the fostering of a balanced, sustainable, and reliable energy market in the EU. The primary focus is to assess auto-regressive forecasting methods and advanced models incorporating moving-average, exploit seasonality of time series data, or those utilising the correlation with exogenous variables. The results are presented for data considering recent history of the most significant energy component at the European energy markets.
Keywords
Data analytics, Forecasting for energy systems, Energy Market, Renewable energy
Conference proceedings
13th DACH+ Conference on Energy Informatics
Numero ( Mese )
February
Publisher
ACM SIGEnergy Energy Informatics Review
Meeting name
13th DACH+ Conference on Energy Informatics
Meeting place
Lugano, Switzerland
Meeting date
October 9-11, 2024
Pages (or article number)
187-189
Diffusion
License
License undefined
Visibility
Public
