Short-term electricity prices: How AI can help you build confidence in the current market volatility


April 28, 2022


Online Event


03:00 pm - 04:00 pm (CET)



In the last few months, the evolution of electricity prices have pushed energy market participants to find newer, more innovative forecasting solutions. Being able to anticipate short-term electricity prices from day-ahead to real-time with the right level of accuracy, such us minimizing absolute errors, is no longer sufficient.

Electricity generators and producers, flexible asset owners, traders, and retailers are now looking for AI-powered solutions that will give them the data and insights they need to make market moves with more confidence in increasingly uncertain times.

During this webinar we'll show you how N-SIDE's AI software can deliver forecasted values along with their associated confidence levels, allowing you to make the best decisions possible. 

What you will learn

  • How to optimise the usage of your flexible asset with AI models
  • How to increase the value of your portfolio on short-term markets with confidence while relying on machine learning models
  • How to keep visibility on the main fundamentals behind short-term electricity prices
  • Which technologies are best suited to build forecasts with sound confidence level estimates


Michael Malcorps Head of Energy Forecasting Product Management

With a background in Business Engineering and the exposure to various advanced analytics start-ups, Michael is passionate about the energy sector and the development of innovative solutions to accelerate the energy transition. After putting a strong focus on the development of N-SIDE Energy activities towards different types of actors, he now has specific expertise in energy forecasting solutions for market participants. Michael now leads the Energy Forecasting Platform team at N-SIDE.

PIERRE ARTOISENET Energy Senior Expert

With a background in physics and statistics, Pierre has built robust statistical analysis and numerical modeling skills, first in the high-energy physics academic community and then in the corporate energy sector. Besides his technical work, Pierre has produced high-quality reports (including international publications in prestigious journals) and presented talks on many occasions. At N-SIDE, Pierre led a technology suite of innovative algorithms for energy price & volume forecasts, and brought breakthroughs in the field of Explainable AI (XAI) to increase interpretability of trained models.

Request the Handout and Replay

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