Power market fundamentals

  • Create power price forecasts and scenarios
  • Get detailed results per power plant per hour
  • Study multi-market, with interconnection capacities
  • Enjoy user-friendly interface and fast calculations
In need of fundamental power market prices? KYOS has the answer. KyPowerFundamentals (KyPF) creates hourly power price forecasts. Use the software to assess the impact of policy changes, or assist with strategic investment decisions and to support trading activities.

KyPF has the unique feature of integrating Monte Carlo simulations into fundamental power market modelling. This provides a much broader perspective on potential future developments than a single forecast.


1. Combine scenario analysis with fundamental modelling

The fundamental market model calculates the expected future power prices based on assumptions for fuel prices, demand, renewable production and interconnection capacities. Some of these assumptions may be quite uncertain, which is why the model works with different scenarios for fuel prices, demand and renewable production. This unique feature allows you to generate joint simulations of fuel and power prices. This broader perspective is essential for better trading and investment decisions.


2. Create future demand and renewable production

For a fundamental hourly optimization, you need detailed inputs for demand and renewable production. Based on capacity growth assumptions, a smart algorithm reshapes historical information into detailed forecasts, seamlessly integrating fundamental capacity forecasts in the KyPF model. Instead of a single forecast for the time series, you can also use a range of scenarios, reflecting the uncertainty in future market conditions.

3. Detailed inputs and outputs per power plant

The model provides detailed inputs for each conventional power plant, including capacities, start curves, efficiencies, operating costs, heat supply, and more. In the outputs we show exactly how each plant is dispatched. This allows you to see the contribution per power station to overall production and carbon emissions. As a result, this detailed information forms a solid basis for your strategic and policy decisions.

4. Optimize energy storage and other flexibility sources

Conventional power stations, running on fossil fuels, are the main price setters in most markets. However, the renewable energy growth is bringing energy storage more to the forefront. The KyPF model incorporates both pump-hydro and other energy storage facilities, such as batteries. Furthermore, it is possible to add other flexibility instruments and demand response mechanisms as well.

5. Optimize interconnection capacities between multiple areas

Power markets are generally interconnected to other power markets. This can be within the same country (such as Japan), or between countries. In KyPF the user can define inputs separately per area, as well as the transport capacities between the areas. The model then performs a joint optimization across all areas, making sure that electricity flows from high priced to low priced areas. Hence you will utilize capacities fully!


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Features of the Power Market Fundamental model

KyPF calculates the optimal dispatch of hundreds or even thousands of power stations. You will get a detailed hourly modelling per power plant, including for instance start curves, maintenance periods, and run-times. Moreover, it models multiple markets simultaneously, thereby optimizing interconnection flows.

Of course we have fully integrated KyPF in the KYOS Analytical Platform. With automated data feeds, you always have up-to-date fundamental curves available.


KyPF goes far beyond a simple merit order or cost minimization model. Instead, it mimics actual behavior in a competitive electricity market: power producers run their plants to maximize revenues, while market prices ensure supply equals demand in every hour.

The KyPF model employs very fast algorithms for the optimal economic hourly dispatch of power stations. We have combined this with a methodology to derive the equilibrium hourly market prices, based on Lagrangian relaxation. The optimization methodology finds the hourly market prices under which the power stations, the energy storage facilities and the interconnection capacities are optimally utilized, and the total production equals the demand in each area.

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