The Power2Sim fundamental model from Montel

There are various modelling approaches for the hourly modelling of future power prices. To simulate power price scenarios up to 2060, Montel uses the Power2Sim fundamental model, which simulates the merit order on an hourly basis and calculates the prices from this. But how exactly does this model work and how does it differ from other approaches? 

A fundamental model describes the basic mechanisms of a system. It is used to predict the behaviour of a system and to map key factors and their interactions. In relation to the electricity market, that means modelling supply and demand, which are influenced by market mechanisms and external factors. This data is mapped mathematically in the system and is then available for further calculations. 

Modelling of the ‘Power2Sim’ fundamental model  

The in-house fundamental model ‘Power2Sim’ is a so-called ‘merit order model’ in which the hourly electricity price is simulated based on the merit order. A demand and supply curve are created for each hour, and the intersection of these curves determines the electricity price. This price is determined by the marginal costs of the most expensive power plant still required to cover demand.  

Thermal power plants

• Thermal power plants are represented by an internal power plant directory containing data on gas, coal and nuclear power plants with an output of more than 20 MW. Specific start-up costs and must-run shares are also considered. Commodity and CO2 prices, which influence marginal costs, are included as external parameters. As commodity and CO2 prices have a major influence on the marginal costs of thermal power plants, they are considered as an additional parameter in the modelling. 

Renewable energies

• Renewable energies are modelled using a Mateo-weather-pattern that scales historical feed-ins to future generations. The weather year 2009 is used for the modelling. The feed-in profiles used for these technologies can be replaced by plant-specific profiles. 

Run-of-river power plants

• Run-of-river power plants are modelled using monthly profiles and thus lead to a monthly base load generation. Electricity generation from reservoirs is modelled using a ‘reservoir operating costs’ model. 

The merit order is determined for the EU27, UK, Norway and Switzerland. The cross-border interconnection capacities, i.e. the imports and exports of electricity between countries, are then analysed. This iterative process equalises the prices until either the prices match or the cross-border interconnection capacities are exhausted. It should be noted that the analysis of cross-border interconnection capacities does not consider any physical level, i.e. actual electricity flows, but only on a theoretical level. As electricity always takes the path of least resistance, it is possible that 80% of the load of a connection is utilised in theory, but only 70% due to the physical current flows.   

An important component of the electricity market is therefore Flow-Based Market Coupling (FBMC), which calculates the transmission capacity using an algorithm that takes into account all lines and electricity flows relevant for trading. This allows the marginal coupling capacities to be determined and utilised more precisely. This feature will also be included in Power2Sim in the future. 

Results and possible applications of Power2Sim

In addition to power prices up to 2060, the results of the model also include the residual load - i.e. demand minus fluctuating renewable energies - imports and exports between the individual countries, the merit order and power plant utilisation, as well as the emissions emitted.   

This data is mainly used in strategy evaluation, investment planning, cost and revenue planning, but also in power plant deployment planning and optimisation, in trading as short-term forecasts and in the analysis of the impact of renewable energies.   

Montel uses the fundamental model to create power price scenarios up to 2060. There are two approaches to collecting relevant input data:    

• In a forecast-based approach, historical data is used and projected into the future. Future events are thus calculated from past data. As various developments are conceivable, each of these developments is combined with a probability in order to achieve a result.    

• This contrasts with the scenario-based approach. In this approach, the future is represented by a consistent network of assumptions about the development of the individual influencing factors in the future. Credible scenario worlds are therefore developed which consider potential future developments in the energy market and which are not dependent on historical data. This makes it possible to anticipate political and geopolitical changes, among other things.   

The advantage of scenarios is that they consistently depict the future through a target state and all decisions that lead to it. This allows the effects of changes to be clearly understood. 

Differences to the PFC model 

An alternative approach to the fundamental model is the econometric approach that can be used with price forward curves (PFC). These calculate hourly electricity prices from historical prices and future forward market prices for the front year. It is based on statistical analyses that include the expansion of renewable energies. The difference is that the PFC looks at historical prices and combines them with forward market prices. The less the focus is on historical prices and external influences are included, the closer the PFC comes to a fundamental model. 

Advantages and disadvantages of the price-forward curve and fundamental models  

The PFC model offers a faster and simpler method for forecasting electricity prices for the next 1-10 years. Seasonal effects and feed-in patterns are anticipated and projected into the future. In contrast to the fundamental model, the PFC looks at the short and medium term. For long-term electricity price simulations (> 10 years) with a consistent data set, fundamental models such as ‘Power2Sim’ are a good alternative, as they simulate the electricity market independently. 

In summary, Power2Sim offers a comprehensive, long-term simulation of electricity markets, providing valuable insights for strategic planning, investment decisions, and the analysis of renewable energy impacts, making it a robust alternative to traditional price-forward curve models for forecasting beyond 10 years.