Long-term power price forecasting in volatile electricity markets

Increasing power market volatility, growing price cannibalization from renewables, and the rise of battery energy storage systems (BESS) are making it essential to capture realistic hourly price patterns in power price forecasts to deliver bankable results.

In this workshop, DNV experts will present the latest evolution of our power price forecasting (PPF) methodology, combining proven fundamental approaches with advanced machine learning techniques to address today’s market challenges.

Designed to deliver highly accurate long-term price forecasts with realistic hourly profiles, DNV’s approach provides market-leading insights into: Baseload power price curves, wind and solar capture prices and hourly price volatility used for BESS revenues forecasts.

In the second part of the workshop, we will demonstrate how these forecasts translate into actionable insights across the two following critical topics: 

• Forecasting negative power prices
  Deep dive into how the PPF model enables robust forecasts of negative price occurrences over the coming years. The session will also examine the impact of recent and upcoming regulatory changes, and what they imply for market dynamics in the long term.  
  
  
• Project capture prices and “P90 of revenues”
  Introduction of DNV’s new service combining years of expertise in wind and solar yield assessments with advanced power price forecasting. By coupling hourly generation profiles with hourly price signals, this approach overcomes the limitations and biases of traditional methods; delivering more reliable forecasts of project revenues and downside risk.

Why attend

By attending this workshop, you will:

• Understand how power price forecasting models work in practice 
• Learn why advanced forecasting methodologies have become essential in today’s power markets 
• Gain insights into the evolution of negative power prices over the coming years and their impact on your projects 
• Discover why traditional revenue estimation approaches are no longer sufficient 
• Explore how an hourly-based methodology provides more accurate and reliable results