Data science for short-term energy trading

Azzurra Casali – Axpo

Short-term energy trading faces unique challenges, including the intermittency of renewable energy sources, market volatility, and the need for rapid, data-driven decision-making. In this discussion, we will explore how to address these issues using data science by integrating time series forecasting, machine learning, and optimization techniques into trading strategies. Real-world use cases from diverse markets and geographies will illustrate the practical implementation of these approaches, guiding attendees to gain valuable insights into the intersection of data science and energy trading.