Introducing – Imbalance Costs Data
This data set enables users to track and compare the costs associated with mismatches between day-ahead forecasted and realised renewable generation across different balancing zones and technologies. The imbalance costs are based on the renewable generation of the whole balancing zone and provide a historical trend for realised imbalance costs for a specific technology in the considered balancing zone.
What Are Imbalance Costs?
Renewable generators incur imbalance costs when the day-ahead forecasted renewable generation deviates from the realised generation levels, leading grid operators to take action to maintain system stability.
These actions can include activating reserve power, participating in short-term markets, or curtailing excess production.
Depending on the costs for the TSO to smooth out the net imbalance of all Balancing Responsible Parties (BRPs) in the system, an imbalance price is determined. Costs are passed on to generators via imbalance charges or reflected in grid fees and market prices.
The realised imbalance costs displayed in the Pexapark platform correspond to the raw costs of such deviations. Even though they do not correspond to the final balancing fees agreed within a balancing contract, they strongly influence these fees.
Why are Imbalance Costs Important?
Understanding imbalance costs is crucial for operational and commercial decision-making. These costs can significantly impact profitability, especially in merchant markets. Knowing how they vary across technologies, countries, or seasons can help in:
Understanding the trends of realised imbalance costs across different markets and technologies
Optimising forecasting of imbalance costs
Informing negotiation of balancing contract pricing and terms
Pexapark Imbalance Costs Data and How it Helps
Data / Feature | Use Case | Benefit |
12 month rolling average absolute (EUR/MWh) | View the direct monetary cost of imbalances, averaged over a 12 month period | Supports evaluation of financial exposure |
12 month rolling average ratio (% of Spot Price) | Understand imbalance costs as a percentage of the average day-ahead spot price for the same perio | Supports analysis of cross-market and cross-technology comparisons |
Imbalance cost data filters for onshore wind, offshore wind, solar and pricing markets | Compare imbalance costs across different markets and technologies | Identify which markets or technologies have the lowest volatility to support procurement and investment decisions |
Export Function | Download data for further analysis | Integrate data into workflows, price and risk modelling for increased accuracy |
How the Data Works
The methodology uses the following input data:
What’s Not Considered:
Intraday market optimisation
Intraday updated forecasts
Real-time dispatch actions
We update data every month after the end of the month.
The estimated realised imbalance costs are based on day-ahead forecast, production and imbalance price data from TSOs and day-ahead spot market prices. They do not include any intraday optimization (i.e. adapting the position in the intraday market, to potentially reduce imbalance volumes), and assumes the difference between day-ahead forecasted and realised generation is fully exposed to imbalance charges.
The costs are averaged over 12 months, on a 12-month rolling basis, to show a continuous trend.
The relative imbalance cost is a ratio of the imbalance cost and the simple average day-ahead price for the 12-month rolling window.
They represent the difference between the revenues that would have been earned with a perfect day-ahead forecast and the actual revenues obtained - based on the day-ahead forecast used for bidding and the forecast error settled at the imbalance price.
The imbalance costs are defined by the following formulae, depending on the system used in the market:
For Dual-Price Systems - e.g. France
| Balancing Zone Long | Balancing Zone Short |
Renewable Asset Long | -> Cost | -> Small or No Cost/Gain |
Renewable Asset Short | -> Small or No Cost/Gain | -> Cost |
For Single-Price Systems - e.g. Germany
| Balancing Zone Long IP < DAP | Balancing Zone Short IP > DAP |
Renewable Asset Long | -> Cost | -> Gain |
Renewable Asset Short | -> Gain | -> Cost |
We normalise the monthly imbalance costs. Therefore, to get the rolling average we must weight by the production.
So the rolling 12-months average is calculated as:
How do I compare markets / technologies?
The comparison feature enables side-by-side analysis of different technologies within the same market (see screenshot). For example, users can compare the relative imbalance costs of offshore and onshore wind in Germany over the past year, identify volatility, and use this insight to inform investment or operational strategy.
What are some Limitations and Assumptions?
Calculations are based on public and estimated data
Intraday optimisation is not factored into the costs
Data is presented “as-is” and does not capture all system-side corrections
Portfolio effects are not accounted for
NOTE: Pexapark does not guarantee the completeness or accuracy of external data sources
The data represents an indication of the realised imbalance cost of an average asset in the balancing zone. The cost of such imbalances for any individual asset in the balancing zone will depend on the correlation between the asset imbalance and that of the system. The more positive this correlation, the more negative it works out on the earnings of the asset. For example, if the system is short and the wind or solar asset produces less than expected, the imbalance is likely to be settled at a high price. In turn, if the imbalance of the asset is supporting the overall system’s stability, and the wind or solar asset produces more than expected in the system is short, it will receive a higher price for the imbalance volume.
In addition, the imbalance cost of a (diversified) portfolio will lead to lower imbalance costs.
How are Imbalance Costs managed in the market?
While the platform focuses on cost visibility, it’s important to understand that system-level efforts to reduce imbalance costs include:
Improved forecasting techniques.
Flexible market mechanisms (e.g. intraday trading).
Investment in energy storage and hybrid assets
Grid reinforcement to reduce congestion
What are the Available Markets, Technologies and Historical Data?
In determining whether to make data available for a given market and technology, we review the historical data for consistency and reliability. The current list below represents those that offer a reasonable view of the market as of 30 April 2025.
The earliest date of the historical data for each market and technology pair is show below.
Market | System | Offshore Wind | Onshore Wind | Solar |
Denmark DK1 | Single price | December 2016 | December 2016 | December 2016 |
Denmark DK2 | Single price |
| December 2016 | December 2016 |
Finland | Single price |
| December 2016 |
|
France | Dual price |
| December 2016 | December 2016 |
Germany | Single price | August 2019 | August 2019 | August 2019 |
Great Britain | Single price |
|
| February 2017 |
Portugal | Dual price |
|
| December 2016 |
Spain | Dual price |
| December 2016 | December 2016 |
Sweden SE3 | Dual price |
| December 2016 |
|