Power price scenario swarms

Simulate 1,000 scenarios to calculate portfolio risks, optimise asset production, and hedge across energy commodities.

Overview

Scenario Swarms calculate power price scenarios more than 1,000 times using our Power2Sim fundamental energy market model. Use them to interpret the probability distribution of power prices, showing you the potential revenues and risks.

With scenarios available out as far as 2065, you receive:

Receive probability distributions for baseload prices and capture prices in annual resolution, characterised by P-values, for example the P90 price. These key figures can refer to one year (annual P-price) or an average over several years (period P-price).

Choose from three different scenarios: Central, Tensions and GoHydrogen to form the basis for your calculations. Choose one or compare the outlook from multiple future paths.

We include follow-up time as standard to make sure you find the scenario swarms plausible and understandable.

Power price scenario Swarms

Simulate risks and opportunities across power markets

In a rapidly changing market, it’s critical to understand how different external shocks could impact power prices. Power Price Scenario Swarms lets you run 1,000 detailed simulations based on our power price scenarios with historical data to assess market risks and opportunities. By modeling extreme events and market shifts, you can plan your strategy with greater confidence and make informed decisions.

Simulate random events to strengthen your strategy

Model the impact of commodity prices, weather, and demand shocks

Our scenario swarms capture the effects of unpredictable variables, such as commodity price changes due to external events, extreme weather events, and electricity demand fluctuations. These random factors are integrated into each simulation, giving you a comprehensive understanding of potential outcomes in trading, investments, and long-term planning.

Explore more in our use case for evaluation PPAs using Swarms: Read in our blog

Build robust revenue models

Use period pricing to forecast revenue with confidence

With period pricing, you can see what revenue levels are achievable under different market situations. For example, the P90 value shows the revenue that can be expected in 90% of cases, ensuring your projections are solid and risk-adjusted. This method helps you develop secure revenue cases, making your financial plans resilient even in uncertain market conditions.

Read more about this in our use case about how to evaluate a large-scale renewable energy plant using Swarms: Read in our Blog