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 in the traditional deterministic fundamental market models.
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 Monte Carlo simulations of fuel prices, demand and renewable production. That is a unique feature, allowing it to generate joint simulations of fuel and power prices. This broader perspective is essential for better trading and investment decisions.
For a fundamental hourly optimization, detailed inputs are required 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, Monte Carlo simulations can be used as well, being on average equal to the time-series forecast.
Detailed inputs are provided 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. This detailed information is the basis for strategic and policy decisions.
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 pump-hydro and other energy storage facilities, such as batteries. Other flexibility instruments and demand response mechanisms can be added as well.
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 until capacities are fully utilized.
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KyPF calculates the optimal dispatch of hundreds or even thousands of power stations. Detailed hourly modelling is done per power plant, including start curves, maintenance periods, runtimes, etc. Multiple markets are simultaneously modelled, optimising interconnection flows.
KyPF is fully integrated in the KYOS Analytical Platform. With automated data feeds, up-to-date fundamental curves are always available.
KyPF goes far beyond a simple merit order or cost minimization model. Instead, it mimics actual behaviour 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. This is combined 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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