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| Abstract | FZJ-2025-05267 |
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2025
Abstract: Forecasting electricity prices, load, and renewable generation has become essential for power system operators, energy traders, and analysts as renewable penetration and market volatility rise across Europe, a trend reflected in the sharp growth of related research, including more than 4,000 papers published in 2024 alone1. Despite a vast body of literature and notable open-access efforts such as Lago et al.2 (2021), the field lacks a widely accepted, continuously updated real-time benchmark [JW1.1]that captures the evolving conditions of modern power markets. As a result, it remains difficult to reliably assess state-of-the-art forecasting performance, hindering consistent and measurable progress, both in research and in commercial practice.Existing studies rely on static historical benchmark datasets2–4, which are useful for comparing relative model performance. However, in a rapidly changing energy system, their results quickly become outdated and offer limited insight into real-time forecasting performance under current system conditions. Furthermore, static benchmarks allow to rely on exogenous regressors that were not available at the time the forecast would have been issued, thereby overlooking key real-time forecasting constraints . At the same time, commercial forecasting solutions remain predominantly closed-source, preventing transparent quality assessment and inhibiting trust in their performance claims (see, e.g., Semmelmann7 (2025) or Stupperich8 (2025)).This paper introduces a benchmark arena for real-time energy forecasting. The platform provides the first open, API-driven environment where researchers and practitioners can submit day-ahead forecasts for electricity prices, load, and renewable generation. [JW2.1]All submissions are evaluated once actual values are published, ensuring assessment under true real-time conditions. Standardized metrics are computed automatically, and a public leaderboard ranks models based on rolling-horizon performance (e.g., the best results over the last 30, 90, or 365 days). This enables systematic comparison of forecasting solutions, quantifying real performance differences and providing an evidence-based view of methodological progress. By continuously reflecting contemporary market dynamics, the benchmark arena establishes a transparent, reproducible, and dynamically evolving reference for forecasting quality.
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