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EEEEEE 2008-2025 EEEEEE 2026 JAN FEB MAR APR MAJ JUN 2026 JUL AVG SEP OKT NOV DEC JUL 19-23, 2026 - Montréal, Canada 2026 IEEE PES General Meeting JUL 23-24, 2026 - Vienna, Austria RESS-2026 JUL 25-27, 2026 - Tokyo, Japan ICGET 2026 JUL 26-29, 2026 - Bellevue, USA ES 2026 JUL 28-31, 2026 - Chengdu, China ICPET 2026 
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MAY 28-29, 2026 - Amsterdam, Netherlands European Electricity Price Forecasting and Modelling 2026 15th European Electricity Price Forecasting and Modelling 2026 28 – 29 May 2026 | Amsterdam, Netherlands The 15th Electricity Price Forecasting & Modelling Conference 2026 unites Europe`s top market analysts, quants, traders, and system operators to explore advanced forecasting techniques, market design changes, volatility drivers, and data-driven modelling innovations shaping the future of electricity price prediction. The 15th Electricity Price Forecasting & Modelling Conference 2026 returns as Europe’s most influential platform for advancing power market forecasting, modelling innovation, and trading strategy. As Europe’s electricity system undergoes unprecedented transformation—driven by rising renewable penetration, flexibility markets, evolving market design, and increasing grid volatility—accurate, data-driven price forecasting has become mission-critical for utilities, traders, TSOs, DSOs, analysts, and investors. This conference brings together leading quants, economists, traders, system operators, modelling experts, and technology innovators to explore cutting-edge forecasting methodologies across short-term, intraday, real-time, balancing, and long-term horizons. Attendees will gain insights into how policy changes, congestion patterns, cross-border flows, climate variability, and extreme weather impact market dynamics and price formation. Through advanced modelling sessions, case studies, interactive panels, and networking opportunities, participants will discover how to integrate new forecasting inputs—such as system reliability indicators, storage behaviour, fuel markets, flexibility signals, and non-traditional datasets—into modern electricity price models.  |