Forecasting Renewable Energy at European Markets

The ambitious energy targets, accelerated by the recent energy crisis, are driving the increase of renewable energy share in gross energy consump- tion. However, the intermittent and seasonal nature of renewable energy sources presents challenges in predicting their production capacity. The abil- ity 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 en- ergy 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 incorporat- ing 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.

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Publication Details

Journal
ACM SIGEnergy Energy Informatics Review
Published
2024-10-01
DOI
https://doi.org/10.1145/3717413.3717430
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
0.00
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article

Forecasting Renewable Energy at European Markets

Olaf Schenk, Juraj Kardoš, Hun Rim
ACM SIGEnergy Energy Informatics Review
Market Dynamics and Volatility
article

Forecasting Renewable Energy at European Markets

Olaf Schenk, Juraj Kardoš, Hun Rim
article en

Abstract

The ambitious energy targets, accelerated by the recent energy crisis, are driving the increase of renewable energy share in gross energy consump- tion. However, the intermittent and seasonal nature of renewable energy sources presents challenges in predicting their production capacity. The abil- ity 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 en- ergy 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 incorporat- ing 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.

ACM SIGEnergy Energy Informatics ReviewVol. 4(4)
Università della Svizzera italiana (CH)
Openalex Percentile: Top 68%
Market Dynamics and Volatility
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