Evaluate your PPA: A case for power price scenario swarms

Navigating Rising Market Prices and Shape Risk in Power Purchase Agreements (PPAs)

Due to the rising futures market prices in 2021, triggered by the gas price crisis, liquidity on the bilateral over-the-counter market has increased - especially on the market for so-called Power Purchase Agreements (PPAs). As a result of the development of PPAs, the players have to be prepared for new risks that need to be managed. In particular, the risk that the weather may change in the short- and long-term leads to increasing uncertainty regarding the structuring of PPA volumes and, in the worst case, can lead to high costs. For this reason, a PPA should always include a certain risk discount, known as shape risk, to consider changes in the structuring costs.

What is shape risk?

Shape risk is a cost factor in the evaluation of a PPA. Shape risk is a generic term for three sub-risks:   

• the risk that the power price curve has a different profile and therefore leads to different revenues when generating electricity  

• the risk that the generation curve looks different (shifted in time, higher or lower feed-in) and therefore changes revenues,  

• the risk that the volume of feed-in could be lower overall (even if the feed-in profile remains the same).   

Together, these three sub-risks comprise the shape risks. The weather has an influence on all three sub-risks, but to different degrees: it plays a major role in the volume of feed-in, while many other factors also play a role in the profile of power prices.  This is where our scenarios swarms and power price scenarios, on the basis of your energy market modelling tool, Power2Sim, comes into play.  

Leveraging scenarios swarms for a PPA assessment  

To navigate the complexities of the electricity market, we use our fundamental model, Power2Sim, and create consistent scenarios, how the influencing factors of the power price develop. However, as we have seen in the electricity market in the past, exogenous shocks such as a slump in demand for electricity, sharp rises in commodity prices, such as the price of gas in 2021/2022, or even fundamental changes in the weather can influence power prices. These exogenous, unpredictable shocks are difficult to model using fundamental modelling. However, the new ‘swarm modelling’ allows such exogenous changes to be modelled and taken into account in asset valuation. The “Swarm-Approch”  simulates various scenarios by considering different weather patterns, economic conditions, and commodity price effects. Here's how it works:  

Scenario Analysis:

Power2Sim runs over 1,000 different scenario simulations with changing input factors. A kind of Monte Carlo simulation is therefore used to create a probability distribution of the power prices. 

Data Inputs:

Data inputs incorporates weather data, economic forecasts, and commodity price trends.  For the weather factor, this means that the underlying weather years vary from run to run. Specifically, this means: for each run, a new sequence of historical weather years, one per model year, is randomly drawn. In order to take future climate changes and their effects on the results of power price scenarios into account, probabilities of occurrence are assumed for individual weather years, which depend on the respective model year. The further into the future the model year is, the higher the probability that a warm weather year will be drawn. 

Probability Distribution:

The output is a probability distribution of the base prices and the market value (capture price) of wind and solar for your selected period. P-values play a decisive role in this context. A P-value indicates the probability of an observed event occurring. Depending on the P-value selected, different values can be derived, ranging from conservative to optimistic estimates. 

This robust approach allows us to provide a detailed analysis of potential market conditions. 

Assessing Shape Risks and Pricing in PPAs Using Power Price Scenarios

The probability distribution generated with the help of the Power price scenarios is invaluable for answering critical questions, such as:  

• Determination of the shape risks for the desired PPA term for solar, onshore wind and offshore wind PPAs at a desired risk level.  

• Determination of base prices for longer PPA terms at a desired risk level.  

• Determination of the capture prices for the above technologies for longer terms at a desired risk level. 

Conclusion  

Many cost components play a role in determining a PPA price. In particular, changing electricity prices and weather fluctuations. By leveraging the power price scenario swarms and our Power2Sim model, you can navigate market complexities and make informed decisions about your PPA evaluation, especially regarding your structuring costs.