EU renewables value tracker

Bruegel’s European Union renewables value tracker quantifies and visualises the economic value of variable renewable energy (VRE) sources across Europe. Building on ENTSO-E Transparency Platform data, it shows the operational and earning patterns of VRE in Europe’s electricity market.

The analysis is based on three metrics.

1. The capacity factor (CF) describes how much of a technology’s maximum technical output potential (installed capacity) is used over a specific period.
   Example: if a solar power plant with an installed capacity of 100 megawatts (MW) generates 50 megawatt hours (MWh) of electricity in a given hour, its capacity factor is 0.5 in that hour.

2. The market value (MV) is the average revenue a technology earns by selling its generated electricity in the wholesale market (in the absence of subsidies). 
   Example: if a given country has an average wholesale price of €100/MWh in a given year, but a specific technology generates electricity during hours with an average market price of €50/MWh, this technology’s market value would be below the average wholesale market price.

3. The capacity revenue (CR) brings the two concepts together: multiplying the CF and MV, it expresses the yearly economic value of one unit of installed generation capacity.
   Example: if a given technology has an average capacity factor of 0.5 and an average market value of €50/MWh in a given country and year, it would result in a capacity revenue of €50/MWh x 0.5 x 8760h = €219,000/MW or €219/kW per year.

Each of these metrics is calculated per year and per country, enabling cross-country comparison and analysis over time.

1 Capacity factor (CF)

For renewables, the CF is influenced primarily by weather conditions and technological performance. The influence of market design is becoming increasingly important, as the generation of renewable electricity must occasionally be curtailed due to insufficient grid capacities, which reduces generation and hence the CF.

As shown in the figure, average CFs vary notably between renewable energy sources. Solar photovoltaic exhibits the lowest average value (0.1), while onshore wind (0.23) and offshore wind (0.36) show higher values. The reason for this is mainly environmental, as solar photovoltaics do not generate at night and produce close to their maximum potential only during midday summer hours.

Wind power CFs are generally higher, with offshore wind power exhibiting larger capacity values than onshore wind power because of higher and more consistent wind speeds on sea compared to land.

Generation technologies differ strongly in how much CFs vary between countries in Europe. While the span between the minimum and maximum average CFs is around 0.1 for onshore wind and 0.15 for offshore wind, the span is almost 0.2 for solar photovoltaics.

Differences in solar CFs can be primarily explained by differences in sunshine length and intensity, with Southern Europe achieving higher values. In contrast, Northern Europe has on average higher wind CFs.

Generally, CFs of variable renewable electricity sources are determined by climatic conditions, therefore values are broadly stable over time. However, values can change slightly over time for various reasons.

Solar photovoltaic CFs have gradually improved in most regions because of advances in module efficiency and tracking systems. Temporal stability in the CFs of solar suggests that annual weather variability exerts a smaller influence than structural differences in solar resource availability.

Wind power CFs have increased slightly across most zones, driven by technological advances (eg larger rotor diameters, higher hub heights) and the upgrading of older fleets. The increase of the CFs is partly dampened by newer installations being placed in less windy spots, as the ‘best’ sites are already taken. Moreover, climatic fluctuations, such as wind droughts in 2021 and above-average conditions in 2023, cause year-to-year volatility.

2 Market value

Renewable energy sources account for an increasing share of Europe’s electricity generation. Unlike conventional thermal generators, which can dispatch the electricity they produce in response to market signals, wind and solar generation are weather-dependent and therefore inherently variable. Consequently, their revenues depend on the interaction between generation patterns and market prices. This relationship is captured by the MV.

Variable renewable energy sources suffer from ‘cannibalisation’: their deployment increases electricity supply, which reduces the wholesale market price. Consequently, the MV decreases and deploying further units of that renewable energy becomes less profitable.

Cross-country differences in MVs remain pronounced across Europe, with no clear geographical pattern. Italy and several eastern European markets exhibit comparatively high solar MVs. This can be attributed to high average electricity prices in recent years, limited deployment of solar photovoltaics and consequently weaker price-cannibalisation effects, which allow solar generation to capture higher average prices. By contrast, Germany and Spain record markedly lower solar MVs, primarily reflecting the impact of rapid capacity expansion and associated cannibalisation.

Wind MVs are comparatively more uniform across Europe, as wind speeds are less correlated between countries, which mitigates intraday cannibalisation, a phenomenon called ‘geographic averaging’.

Before 2021, the MV of all renewables declined gradually, particularly in markets with high shares of solar power in their electricity mixes, such as Spain. Increasing solar generation depressed prices during sunny hours.

During the 2021-2022 energy crisis, wholesale prices increased strongly because of increases in natural gas prices. Consequently, the MVs of all generation technologies, including renewables of all output profiles, surged to record highs. Post-crisis, values have decreased somewhat but remain above pre-crisis levels.

3 Capacity revenue (CR)

A higher CR (denoted in €/kW) is a consequence of a renewable technology’s generation profile aligning well with periods of high market prices. In such cases, the technology not only operates efficiently, which is reflected by a high CF, but also earns a relatively high MV for its output. Conversely, when generation occurs predominantly during times of lower prices, such as when many similar technologies are producing simultaneously, revenues per unit of installed capacity decline, even if the physical output remains similar. This cannibalisation reduces the economic return on additional capacity. 

Therefore, CR captures both technical performance and market context. It illustrates how effectively a technology converts installed capacity into economic value.

Prior to the energy crisis, Spain and Italy had similar solar CRs, reflecting similar utilisation and market values. Following the crisis, however, Italy’s MV increased more sharply than Spain’s. When downward pressure on capture prices - the average prices solar actually earns during its generation hours - set in, both countries experienced declines, but Spain’s drop was steeper. Spain’s heavier solar saturation tends to depress midday prices more strongly, reducing MV and thus CRs, despite a similar generation profile to Italy.

As variable renewables have expanded, the marginal CRs of additional solar and, to a lesser extent, wind, have tended to decline. More output coincides with the same hours, pushing prices down and reducing the incremental value of new generation. 

During the 2021–2022 energy-price shock, CRs rose temporarily with the increase in wholesale prices, but 2024 saw broad deflation of capture prices, pulling MVs back down, despite high renewables output.

4 Methodology

Data sources

The data shown here is primarily from the  ENTSO-E Transparency Platform. Market price and generation series reported at 15, 30 and 60 minute intervals for solar and wind are harmonised, and annual installed capacity data is incorporated for all European bidding zones.

Prices for the United Kingdom and Poland are converted to euros using the European Central Bank’s (ECB) daily reference exchange rates, with a fallback up to the three previously recorded days when rates are missing. 

Installed capacity data from ENTSO-E’s Transparency Platform represents values recorded at the end of each year; these are used as the reference capacity for the subsequent year’s calculations.

For solar, ENTSO-E’s Transparency Platform aggregates only production units exceeding 1 MW when reporting yearly installed capacity, whereas generation data includes all units. Therefore, we use EMBER’s installed capacity data for solar, as they provide a more comprehensive estimate. The only exception is Norway, for which we retain ENTSO-E’s Transparency Platform installed capacity data.

Where data is missing in either ENTSO-E’s Transparency Platform or EMBER, we complement it with the following national sources (specifically, for solar and wind):

• Terna (Italy’s transmission system operator), and 

• OSS (Statistics Sweden’s energy office).

For Italy and Sweden, installed wind power capacities are reported without separating onshore and offshore. For these two countries, we use onshore wind capacity, as installed offshore wind power capacities are close to zero.

For Germany, because of a bidding zone split with Austria, we use price data from the Open Energy Tracker (which is based on SMARD by Germany’s Federal Network Agency). We rely on this source, as Germany is treated as a single country in that dataset.

For the Netherlands, we use solar generation data from the Netherlands energy dashboard because ENTSO-E’s Transparency Platform is inaccurate for this specific zone and technology.

Data limitations

As explained above, we rely on data from ENTSO-E’s Transparency Platform, supplemented by national sources. Differences in data definitions, aggregation thresholds and reporting methods can lead to discrepancies. We therefore encourage users to inform us of any inconsistencies they identify so we can improve data quality as needed.

Definition of indicators

The section below describes the definitions of the indicators shown in this tracker.

The capacity factor (CF) measures the utilisation of installed capacity over a specific period. It is calculated as the ratio of electricity generated to the theoretical maximum that could have been generated if the technology had operated at full capacity during that period. CFs are given in the range of [0, 1]. We show yearly average CFs.

The market value (MV) quantifies the average revenue earned by a technology, regardless of subsidies (Hirth, 2013). It is obtained by weighting hourly (or sub-hourly) market prices by actual generation, thereby reflecting the temporal relationship between production and price levels. This generation-weighted average price captures the extent to which a technology’s output aligns with high- or low-price periods. 

The capacity revenue (CR) combines these two dimensions (quantity and price) into a single measure of economic performance. Multiplying CF and MV and the total number of hours in a year yields the annualised economic value of one kilowatt of installed capacity, expressed in euros per kilowatt per year (€/kW/yr). This metric represents how effectively an installed unit of renewable capacity converts technical potential into economic return under prevailing market conditions. The European averages are calculated as a generation-weighted average across all zones.

References

Hirth, L. (2013) ‘The market value of variable renewables: The effect of solar wind power variability on their relative price’, Energy Economics (38): 218-236, available at https://doi.org/10.1016/j.eneco.2013.02.004