Tackling energy price volatility: a smarter approach to price forecasting

Stable and competitive energy prices are crucial for businesses to thrive and for Europe to be competitive on the global stage. However, electricity prices can fluctuate much more than prices on other markets, with daily variations up to 20 times those of stock markets and hourly volatility over 1000%. Their volatility can be influenced by numerous factors, such as weather, demand shifts, renewable energy production, and market disruptions.  

Businesses and consumers rely on forecasts to navigate this complex market, but traditional forecasting models struggle with extreme price variations, which can distort predictions and make it difficult for energy suppliers, policymakers, and industries to plan ahead and avoid shortages and price shocks. 

A novel approach 

A recent JRC study published in Applied Energy proposes a new method that could improve prediction accuracy. The study introduces an innovative filtering technique that refines historical price data before applying forecasting models. The technique uses advanced statistical methods to detect and adjust extreme price fluctuations while preserving essential market trends.  

When tested on a two-year window across six different electricity markets and on several forecasting models, the new method consistently outperformed traditional approaches, reducing forecasting average errors by up to 4%. This may seem minor, but studies show that improvements of even 1% in forecasting claims could translate to savings of ca. €1.3 million per year for a typical mid-sized energy utility.  

By enabling more precise forecasting, this new approach could support the integration of renewable energy and the stability of electricity markets, help mitigate financial risks, and contribute to a more resilient and sustainable energy future.

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Accurate predictions for a sustainable future 

This research highlights the potential of smarter data handling in improving electricity price forecasting. With reasonable computational costs and broad applicability, the method offers a practical solution for real-world energy challenges. As the market continues to evolve, leveraging such innovations will be essential to ensure economic stability and sustainability. 

Accurate electricity price forecasting is crucial for supporting the European Union’s energy policies, particularly in the context of the EU Green Deal, and efforts to integrate more renewable energy sources into the power grid. Improved forecasting helps stabilise electricity markets, reduces financial risks, and makes renewable energy use more efficient.  

Related content 

Enhancing electricity price forecasting accuracy: A novel filtering strategy for improved out-of-sample predictions 

EU Green Deal